Run the Known Sub-Sequence Algorithm to compare the performance of imputation methods on a time series of interest
Usage
kssa(
x_ts,
start_methods,
actual_methods,
segments = 5,
iterations = 10,
percentmd = 0.2,
seed = 1234
)Arguments
- x_ts
Time series object
tscontaining missing data (NA)- start_methods
String vector. The method or methods to start the algorithm. Same as for actual_methods
- actual_methods
The imputation methods to be compared and validated. It can be a string vector containing the following You can choose between the following:
"all" - compare among all methods automatically - Default
"auto.arima" - State space representation of an ARIMA model
"StructTS" - State space representation of a structural model
"seadec" - Seasonal decomposition with Kalman smoothing
"linear_i" - Linear interpolation
"spline_i" - Spline interpolation
"stine_i" - Stineman interpolation
"simple_ma" - Simple moving average
"linear_ma" - Linear moving average
"exponential_ma" - Exponential moving average
"locf" - Last observation carried forward
"stl" - Seasonal and trend decomposition with Loess
For further details on these imputation methods please check packages imputeTS and forecast
- segments
Integer. Into how many segments the time series will be divided
- iterations
Integer. How many iterations to run
- percentmd
Numeric. Percentage of missing data. Must match with the true percentage of missing data in x_ts
- seed
Numeric. Random seed to choose
Value
A list of results to be plotted with function kssa_plot for easy interpretation
References
Benavides, I. F., Santacruz, M., Romero-Leiton, J. P., Barreto, C., & Selvaraj, J. J. (2022). Assessing methods for multiple imputation of systematic missing data in marine fisheries time series with a new validation algorithm. Aquaculture and Fisheries. Full text publication.
Examples
# \donttest{
# Example 1: Compare all imputation methods
library("kssa")
library("imputeTS")
# Create 20% random missing data in tsAirgapComplete time series from imputeTS
airgap_na <- missMethods::delete_MCAR(as.data.frame(tsAirgapComplete), 0.2)
# Convert to time series object
airgap_na_ts <- ts(airgap_na, start = c(1959, 1), end = c(1997, 12), frequency = 12)
# Apply the kssa algorithm with 5 segments, 10 iterations, 20% of missing data,
# compare among all available methods in the package.
# Remember that percentmd must match with
# the real percentage of missing data in the input time series
results_kssa <- kssa(airgap_na_ts,
start_methods = "all",
actual_methods = "all",
segments = 5,
iterations = 10,
percentmd = 0.2
)
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
#> Warning: No seasonality information for dataset could be found, going on without decomposition.
#> Setting find_frequency=TRUE might be an option.
# Print and check results
results_kssa
#> [[1]]
#> $start_methods
#> [1] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [5] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [9] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [13] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [17] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [21] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [25] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [29] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [33] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [37] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [41] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [45] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [49] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [53] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [57] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [61] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [65] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [69] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [73] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [77] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [81] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [85] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [89] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [93] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [97] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [101] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [105] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [109] "auto.arima" "auto.arima" "StructTS" "StructTS"
#> [113] "StructTS" "StructTS" "StructTS" "StructTS"
#> [117] "StructTS" "StructTS" "StructTS" "StructTS"
#> [121] "StructTS" "StructTS" "StructTS" "StructTS"
#> [125] "StructTS" "StructTS" "StructTS" "StructTS"
#> [129] "StructTS" "StructTS" "StructTS" "StructTS"
#> [133] "StructTS" "StructTS" "StructTS" "StructTS"
#> [137] "StructTS" "StructTS" "StructTS" "StructTS"
#> [141] "StructTS" "StructTS" "StructTS" "StructTS"
#> [145] "StructTS" "StructTS" "StructTS" "StructTS"
#> [149] "StructTS" "StructTS" "StructTS" "StructTS"
#> [153] "StructTS" "StructTS" "StructTS" "StructTS"
#> [157] "StructTS" "StructTS" "StructTS" "StructTS"
#> [161] "StructTS" "StructTS" "StructTS" "StructTS"
#> [165] "StructTS" "StructTS" "StructTS" "StructTS"
#> [169] "StructTS" "StructTS" "StructTS" "StructTS"
#> [173] "StructTS" "StructTS" "StructTS" "StructTS"
#> [177] "StructTS" "StructTS" "StructTS" "StructTS"
#> [181] "StructTS" "StructTS" "StructTS" "StructTS"
#> [185] "StructTS" "StructTS" "StructTS" "StructTS"
#> [189] "StructTS" "StructTS" "StructTS" "StructTS"
#> [193] "StructTS" "StructTS" "StructTS" "StructTS"
#> [197] "StructTS" "StructTS" "StructTS" "StructTS"
#> [201] "StructTS" "StructTS" "StructTS" "StructTS"
#> [205] "StructTS" "StructTS" "StructTS" "StructTS"
#> [209] "StructTS" "StructTS" "StructTS" "StructTS"
#> [213] "StructTS" "StructTS" "StructTS" "StructTS"
#> [217] "StructTS" "StructTS" "StructTS" "StructTS"
#> [221] "linear_i" "linear_i" "linear_i" "linear_i"
#> [225] "linear_i" "linear_i" "linear_i" "linear_i"
#> [229] "linear_i" "linear_i" "linear_i" "linear_i"
#> [233] "linear_i" "linear_i" "linear_i" "linear_i"
#> [237] "linear_i" "linear_i" "linear_i" "linear_i"
#> [241] "linear_i" "linear_i" "linear_i" "linear_i"
#> [245] "linear_i" "linear_i" "linear_i" "linear_i"
#> [249] "linear_i" "linear_i" "linear_i" "linear_i"
#> [253] "linear_i" "linear_i" "linear_i" "linear_i"
#> [257] "linear_i" "linear_i" "linear_i" "linear_i"
#> [261] "linear_i" "linear_i" "linear_i" "linear_i"
#> [265] "linear_i" "linear_i" "linear_i" "linear_i"
#> [269] "linear_i" "linear_i" "linear_i" "linear_i"
#> [273] "linear_i" "linear_i" "linear_i" "linear_i"
#> [277] "linear_i" "linear_i" "linear_i" "linear_i"
#> [281] "linear_i" "linear_i" "linear_i" "linear_i"
#> [285] "linear_i" "linear_i" "linear_i" "linear_i"
#> [289] "linear_i" "linear_i" "linear_i" "linear_i"
#> [293] "linear_i" "linear_i" "linear_i" "linear_i"
#> [297] "linear_i" "linear_i" "linear_i" "linear_i"
#> [301] "linear_i" "linear_i" "linear_i" "linear_i"
#> [305] "linear_i" "linear_i" "linear_i" "linear_i"
#> [309] "linear_i" "linear_i" "linear_i" "linear_i"
#> [313] "linear_i" "linear_i" "linear_i" "linear_i"
#> [317] "linear_i" "linear_i" "linear_i" "linear_i"
#> [321] "linear_i" "linear_i" "linear_i" "linear_i"
#> [325] "linear_i" "linear_i" "linear_i" "linear_i"
#> [329] "linear_i" "linear_i" "spline_i" "spline_i"
#> [333] "spline_i" "spline_i" "spline_i" "spline_i"
#> [337] "spline_i" "spline_i" "spline_i" "spline_i"
#> [341] "spline_i" "spline_i" "spline_i" "spline_i"
#> [345] "spline_i" "spline_i" "spline_i" "spline_i"
#> [349] "spline_i" "spline_i" "spline_i" "spline_i"
#> [353] "spline_i" "spline_i" "spline_i" "spline_i"
#> [357] "spline_i" "spline_i" "spline_i" "spline_i"
#> [361] "spline_i" "spline_i" "spline_i" "spline_i"
#> [365] "spline_i" "spline_i" "spline_i" "spline_i"
#> [369] "spline_i" "spline_i" "spline_i" "spline_i"
#> [373] "spline_i" "spline_i" "spline_i" "spline_i"
#> [377] "spline_i" "spline_i" "spline_i" "spline_i"
#> [381] "spline_i" "spline_i" "spline_i" "spline_i"
#> [385] "spline_i" "spline_i" "spline_i" "spline_i"
#> [389] "spline_i" "spline_i" "spline_i" "spline_i"
#> [393] "spline_i" "spline_i" "spline_i" "spline_i"
#> [397] "spline_i" "spline_i" "spline_i" "spline_i"
#> [401] "spline_i" "spline_i" "spline_i" "spline_i"
#> [405] "spline_i" "spline_i" "spline_i" "spline_i"
#> [409] "spline_i" "spline_i" "spline_i" "spline_i"
#> [413] "spline_i" "spline_i" "spline_i" "spline_i"
#> [417] "spline_i" "spline_i" "spline_i" "spline_i"
#> [421] "spline_i" "spline_i" "spline_i" "spline_i"
#> [425] "spline_i" "spline_i" "spline_i" "spline_i"
#> [429] "spline_i" "spline_i" "spline_i" "spline_i"
#> [433] "spline_i" "spline_i" "spline_i" "spline_i"
#> [437] "spline_i" "spline_i" "spline_i" "spline_i"
#> [441] "stine_i" "stine_i" "stine_i" "stine_i"
#> [445] "stine_i" "stine_i" "stine_i" "stine_i"
#> [449] "stine_i" "stine_i" "stine_i" "stine_i"
#> [453] "stine_i" "stine_i" "stine_i" "stine_i"
#> [457] "stine_i" "stine_i" "stine_i" "stine_i"
#> [461] "stine_i" "stine_i" "stine_i" "stine_i"
#> [465] "stine_i" "stine_i" "stine_i" "stine_i"
#> [469] "stine_i" "stine_i" "stine_i" "stine_i"
#> [473] "stine_i" "stine_i" "stine_i" "stine_i"
#> [477] "stine_i" "stine_i" "stine_i" "stine_i"
#> [481] "stine_i" "stine_i" "stine_i" "stine_i"
#> [485] "stine_i" "stine_i" "stine_i" "stine_i"
#> [489] "stine_i" "stine_i" "stine_i" "stine_i"
#> [493] "stine_i" "stine_i" "stine_i" "stine_i"
#> [497] "stine_i" "stine_i" "stine_i" "stine_i"
#> [501] "stine_i" "stine_i" "stine_i" "stine_i"
#> [505] "stine_i" "stine_i" "stine_i" "stine_i"
#> [509] "stine_i" "stine_i" "stine_i" "stine_i"
#> [513] "stine_i" "stine_i" "stine_i" "stine_i"
#> [517] "stine_i" "stine_i" "stine_i" "stine_i"
#> [521] "stine_i" "stine_i" "stine_i" "stine_i"
#> [525] "stine_i" "stine_i" "stine_i" "stine_i"
#> [529] "stine_i" "stine_i" "stine_i" "stine_i"
#> [533] "stine_i" "stine_i" "stine_i" "stine_i"
#> [537] "stine_i" "stine_i" "stine_i" "stine_i"
#> [541] "stine_i" "stine_i" "stine_i" "stine_i"
#> [545] "stine_i" "stine_i" "stine_i" "stine_i"
#> [549] "stine_i" "stine_i" "simple_ma" "simple_ma"
#> [553] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [557] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [561] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [565] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [569] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [573] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [577] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [581] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [585] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [589] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [593] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [597] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [601] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [605] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [609] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [613] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [617] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [621] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [625] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [629] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [633] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [637] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [641] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [645] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [649] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [653] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [657] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [661] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [665] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [669] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [673] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [677] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [681] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [685] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [689] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [693] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [697] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [701] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [705] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [709] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [713] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [717] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [721] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [725] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [729] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [733] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [737] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [741] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [745] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [749] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [753] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [757] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [761] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [765] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [769] "linear_ma" "linear_ma" "exponential_ma" "exponential_ma"
#> [773] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [777] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [781] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [785] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [789] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [793] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [797] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [801] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [805] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [809] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [813] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [817] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [821] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [825] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [829] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [833] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [837] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [841] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [845] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [849] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [853] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [857] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [861] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [865] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [869] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [873] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [877] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [881] "seadec" "seadec" "seadec" "seadec"
#> [885] "seadec" "seadec" "seadec" "seadec"
#> [889] "seadec" "seadec" "seadec" "seadec"
#> [893] "seadec" "seadec" "seadec" "seadec"
#> [897] "seadec" "seadec" "seadec" "seadec"
#> [901] "seadec" "seadec" "seadec" "seadec"
#> [905] "seadec" "seadec" "seadec" "seadec"
#> [909] "seadec" "seadec" "seadec" "seadec"
#> [913] "seadec" "seadec" "seadec" "seadec"
#> [917] "seadec" "seadec" "seadec" "seadec"
#> [921] "seadec" "seadec" "seadec" "seadec"
#> [925] "seadec" "seadec" "seadec" "seadec"
#> [929] "seadec" "seadec" "seadec" "seadec"
#> [933] "seadec" "seadec" "seadec" "seadec"
#> [937] "seadec" "seadec" "seadec" "seadec"
#> [941] "seadec" "seadec" "seadec" "seadec"
#> [945] "seadec" "seadec" "seadec" "seadec"
#> [949] "seadec" "seadec" "seadec" "seadec"
#> [953] "seadec" "seadec" "seadec" "seadec"
#> [957] "seadec" "seadec" "seadec" "seadec"
#> [961] "seadec" "seadec" "seadec" "seadec"
#> [965] "seadec" "seadec" "seadec" "seadec"
#> [969] "seadec" "seadec" "seadec" "seadec"
#> [973] "seadec" "seadec" "seadec" "seadec"
#> [977] "seadec" "seadec" "seadec" "seadec"
#> [981] "seadec" "seadec" "seadec" "seadec"
#> [985] "seadec" "seadec" "seadec" "seadec"
#> [989] "seadec" "seadec" "locf" "locf"
#> [993] "locf" "locf" "locf" "locf"
#> [997] "locf" "locf" "locf" "locf"
#> [1001] "locf" "locf" "locf" "locf"
#> [1005] "locf" "locf" "locf" "locf"
#> [1009] "locf" "locf" "locf" "locf"
#> [1013] "locf" "locf" "locf" "locf"
#> [1017] "locf" "locf" "locf" "locf"
#> [1021] "locf" "locf" "locf" "locf"
#> [1025] "locf" "locf" "locf" "locf"
#> [1029] "locf" "locf" "locf" "locf"
#> [1033] "locf" "locf" "locf" "locf"
#> [1037] "locf" "locf" "locf" "locf"
#> [1041] "locf" "locf" "locf" "locf"
#> [1045] "locf" "locf" "locf" "locf"
#> [1049] "locf" "locf" "locf" "locf"
#> [1053] "locf" "locf" "locf" "locf"
#> [1057] "locf" "locf" "locf" "locf"
#> [1061] "locf" "locf" "locf" "locf"
#> [1065] "locf" "locf" "locf" "locf"
#> [1069] "locf" "locf" "locf" "locf"
#> [1073] "locf" "locf" "locf" "locf"
#> [1077] "locf" "locf" "locf" "locf"
#> [1081] "locf" "locf" "locf" "locf"
#> [1085] "locf" "locf" "locf" "locf"
#> [1089] "locf" "locf" "locf" "locf"
#> [1093] "locf" "locf" "locf" "locf"
#> [1097] "locf" "locf" "locf" "locf"
#> [1101] "stl" "stl" "stl" "stl"
#> [1105] "stl" "stl" "stl" "stl"
#> [1109] "stl" "stl" "stl" "stl"
#> [1113] "stl" "stl" "stl" "stl"
#> [1117] "stl" "stl" "stl" "stl"
#> [1121] "stl" "stl" "stl" "stl"
#> [1125] "stl" "stl" "stl" "stl"
#> [1129] "stl" "stl" "stl" "stl"
#> [1133] "stl" "stl" "stl" "stl"
#> [1137] "stl" "stl" "stl" "stl"
#> [1141] "stl" "stl" "stl" "stl"
#> [1145] "stl" "stl" "stl" "stl"
#> [1149] "stl" "stl" "stl" "stl"
#> [1153] "stl" "stl" "stl" "stl"
#> [1157] "stl" "stl" "stl" "stl"
#> [1161] "stl" "stl" "stl" "stl"
#> [1165] "stl" "stl" "stl" "stl"
#> [1169] "stl" "stl" "stl" "stl"
#> [1173] "stl" "stl" "stl" "stl"
#> [1177] "stl" "stl" "stl" "stl"
#> [1181] "stl" "stl" "stl" "stl"
#> [1185] "stl" "stl" "stl" "stl"
#> [1189] "stl" "stl" "stl" "stl"
#> [1193] "stl" "stl" "stl" "stl"
#> [1197] "stl" "stl" "stl" "stl"
#> [1201] "stl" "stl" "stl" "stl"
#> [1205] "stl" "stl" "stl" "stl"
#> [1209] "stl" "stl"
#>
#> $actual_methods
#> [1] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [5] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [9] "seadec" "locf" "stl" "auto.arima"
#> [13] "StructTS" "linear_i" "spline_i" "stine_i"
#> [17] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [21] "locf" "stl" "auto.arima" "StructTS"
#> [25] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [29] "linear_ma" "exponential_ma" "seadec" "locf"
#> [33] "stl" "auto.arima" "StructTS" "linear_i"
#> [37] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [41] "exponential_ma" "seadec" "locf" "stl"
#> [45] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [49] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [53] "seadec" "locf" "stl" "auto.arima"
#> [57] "StructTS" "linear_i" "spline_i" "stine_i"
#> [61] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [65] "locf" "stl" "auto.arima" "StructTS"
#> [69] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [73] "linear_ma" "exponential_ma" "seadec" "locf"
#> [77] "stl" "auto.arima" "StructTS" "linear_i"
#> [81] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [85] "exponential_ma" "seadec" "locf" "stl"
#> [89] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [93] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [97] "seadec" "locf" "stl" "auto.arima"
#> [101] "StructTS" "linear_i" "spline_i" "stine_i"
#> [105] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [109] "locf" "stl" "auto.arima" "StructTS"
#> [113] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [117] "linear_ma" "exponential_ma" "seadec" "locf"
#> [121] "stl" "auto.arima" "StructTS" "linear_i"
#> [125] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [129] "exponential_ma" "seadec" "locf" "stl"
#> [133] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [137] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [141] "seadec" "locf" "stl" "auto.arima"
#> [145] "StructTS" "linear_i" "spline_i" "stine_i"
#> [149] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [153] "locf" "stl" "auto.arima" "StructTS"
#> [157] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [161] "linear_ma" "exponential_ma" "seadec" "locf"
#> [165] "stl" "auto.arima" "StructTS" "linear_i"
#> [169] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [173] "exponential_ma" "seadec" "locf" "stl"
#> [177] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [181] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [185] "seadec" "locf" "stl" "auto.arima"
#> [189] "StructTS" "linear_i" "spline_i" "stine_i"
#> [193] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [197] "locf" "stl" "auto.arima" "StructTS"
#> [201] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [205] "linear_ma" "exponential_ma" "seadec" "locf"
#> [209] "stl" "auto.arima" "StructTS" "linear_i"
#> [213] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [217] "exponential_ma" "seadec" "locf" "stl"
#> [221] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [225] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [229] "seadec" "locf" "stl" "auto.arima"
#> [233] "StructTS" "linear_i" "spline_i" "stine_i"
#> [237] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [241] "locf" "stl" "auto.arima" "StructTS"
#> [245] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [249] "linear_ma" "exponential_ma" "seadec" "locf"
#> [253] "stl" "auto.arima" "StructTS" "linear_i"
#> [257] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [261] "exponential_ma" "seadec" "locf" "stl"
#> [265] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [269] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [273] "seadec" "locf" "stl" "auto.arima"
#> [277] "StructTS" "linear_i" "spline_i" "stine_i"
#> [281] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [285] "locf" "stl" "auto.arima" "StructTS"
#> [289] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [293] "linear_ma" "exponential_ma" "seadec" "locf"
#> [297] "stl" "auto.arima" "StructTS" "linear_i"
#> [301] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [305] "exponential_ma" "seadec" "locf" "stl"
#> [309] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [313] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [317] "seadec" "locf" "stl" "auto.arima"
#> [321] "StructTS" "linear_i" "spline_i" "stine_i"
#> [325] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [329] "locf" "stl" "auto.arima" "StructTS"
#> [333] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [337] "linear_ma" "exponential_ma" "seadec" "locf"
#> [341] "stl" "auto.arima" "StructTS" "linear_i"
#> [345] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [349] "exponential_ma" "seadec" "locf" "stl"
#> [353] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [357] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [361] "seadec" "locf" "stl" "auto.arima"
#> [365] "StructTS" "linear_i" "spline_i" "stine_i"
#> [369] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [373] "locf" "stl" "auto.arima" "StructTS"
#> [377] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [381] "linear_ma" "exponential_ma" "seadec" "locf"
#> [385] "stl" "auto.arima" "StructTS" "linear_i"
#> [389] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [393] "exponential_ma" "seadec" "locf" "stl"
#> [397] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [401] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [405] "seadec" "locf" "stl" "auto.arima"
#> [409] "StructTS" "linear_i" "spline_i" "stine_i"
#> [413] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [417] "locf" "stl" "auto.arima" "StructTS"
#> [421] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [425] "linear_ma" "exponential_ma" "seadec" "locf"
#> [429] "stl" "auto.arima" "StructTS" "linear_i"
#> [433] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [437] "exponential_ma" "seadec" "locf" "stl"
#> [441] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [445] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [449] "seadec" "locf" "stl" "auto.arima"
#> [453] "StructTS" "linear_i" "spline_i" "stine_i"
#> [457] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [461] "locf" "stl" "auto.arima" "StructTS"
#> [465] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [469] "linear_ma" "exponential_ma" "seadec" "locf"
#> [473] "stl" "auto.arima" "StructTS" "linear_i"
#> [477] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [481] "exponential_ma" "seadec" "locf" "stl"
#> [485] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [489] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [493] "seadec" "locf" "stl" "auto.arima"
#> [497] "StructTS" "linear_i" "spline_i" "stine_i"
#> [501] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [505] "locf" "stl" "auto.arima" "StructTS"
#> [509] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [513] "linear_ma" "exponential_ma" "seadec" "locf"
#> [517] "stl" "auto.arima" "StructTS" "linear_i"
#> [521] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [525] "exponential_ma" "seadec" "locf" "stl"
#> [529] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [533] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [537] "seadec" "locf" "stl" "auto.arima"
#> [541] "StructTS" "linear_i" "spline_i" "stine_i"
#> [545] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [549] "locf" "stl" "auto.arima" "StructTS"
#> [553] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [557] "linear_ma" "exponential_ma" "seadec" "locf"
#> [561] "stl" "auto.arima" "StructTS" "linear_i"
#> [565] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [569] "exponential_ma" "seadec" "locf" "stl"
#> [573] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [577] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [581] "seadec" "locf" "stl" "auto.arima"
#> [585] "StructTS" "linear_i" "spline_i" "stine_i"
#> [589] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [593] "locf" "stl" "auto.arima" "StructTS"
#> [597] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [601] "linear_ma" "exponential_ma" "seadec" "locf"
#> [605] "stl" "auto.arima" "StructTS" "linear_i"
#> [609] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [613] "exponential_ma" "seadec" "locf" "stl"
#> [617] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [621] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [625] "seadec" "locf" "stl" "auto.arima"
#> [629] "StructTS" "linear_i" "spline_i" "stine_i"
#> [633] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [637] "locf" "stl" "auto.arima" "StructTS"
#> [641] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [645] "linear_ma" "exponential_ma" "seadec" "locf"
#> [649] "stl" "auto.arima" "StructTS" "linear_i"
#> [653] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [657] "exponential_ma" "seadec" "locf" "stl"
#> [661] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [665] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [669] "seadec" "locf" "stl" "auto.arima"
#> [673] "StructTS" "linear_i" "spline_i" "stine_i"
#> [677] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [681] "locf" "stl" "auto.arima" "StructTS"
#> [685] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [689] "linear_ma" "exponential_ma" "seadec" "locf"
#> [693] "stl" "auto.arima" "StructTS" "linear_i"
#> [697] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [701] "exponential_ma" "seadec" "locf" "stl"
#> [705] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [709] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [713] "seadec" "locf" "stl" "auto.arima"
#> [717] "StructTS" "linear_i" "spline_i" "stine_i"
#> [721] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [725] "locf" "stl" "auto.arima" "StructTS"
#> [729] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [733] "linear_ma" "exponential_ma" "seadec" "locf"
#> [737] "stl" "auto.arima" "StructTS" "linear_i"
#> [741] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [745] "exponential_ma" "seadec" "locf" "stl"
#> [749] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [753] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [757] "seadec" "locf" "stl" "auto.arima"
#> [761] "StructTS" "linear_i" "spline_i" "stine_i"
#> [765] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [769] "locf" "stl" "auto.arima" "StructTS"
#> [773] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [777] "linear_ma" "exponential_ma" "seadec" "locf"
#> [781] "stl" "auto.arima" "StructTS" "linear_i"
#> [785] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [789] "exponential_ma" "seadec" "locf" "stl"
#> [793] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [797] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [801] "seadec" "locf" "stl" "auto.arima"
#> [805] "StructTS" "linear_i" "spline_i" "stine_i"
#> [809] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [813] "locf" "stl" "auto.arima" "StructTS"
#> [817] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [821] "linear_ma" "exponential_ma" "seadec" "locf"
#> [825] "stl" "auto.arima" "StructTS" "linear_i"
#> [829] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [833] "exponential_ma" "seadec" "locf" "stl"
#> [837] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [841] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [845] "seadec" "locf" "stl" "auto.arima"
#> [849] "StructTS" "linear_i" "spline_i" "stine_i"
#> [853] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [857] "locf" "stl" "auto.arima" "StructTS"
#> [861] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [865] "linear_ma" "exponential_ma" "seadec" "locf"
#> [869] "stl" "auto.arima" "StructTS" "linear_i"
#> [873] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [877] "exponential_ma" "seadec" "locf" "stl"
#> [881] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [885] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [889] "seadec" "locf" "stl" "auto.arima"
#> [893] "StructTS" "linear_i" "spline_i" "stine_i"
#> [897] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [901] "locf" "stl" "auto.arima" "StructTS"
#> [905] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [909] "linear_ma" "exponential_ma" "seadec" "locf"
#> [913] "stl" "auto.arima" "StructTS" "linear_i"
#> [917] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [921] "exponential_ma" "seadec" "locf" "stl"
#> [925] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [929] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [933] "seadec" "locf" "stl" "auto.arima"
#> [937] "StructTS" "linear_i" "spline_i" "stine_i"
#> [941] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [945] "locf" "stl" "auto.arima" "StructTS"
#> [949] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [953] "linear_ma" "exponential_ma" "seadec" "locf"
#> [957] "stl" "auto.arima" "StructTS" "linear_i"
#> [961] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [965] "exponential_ma" "seadec" "locf" "stl"
#> [969] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [973] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [977] "seadec" "locf" "stl" "auto.arima"
#> [981] "StructTS" "linear_i" "spline_i" "stine_i"
#> [985] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [989] "locf" "stl" "auto.arima" "StructTS"
#> [993] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [997] "linear_ma" "exponential_ma" "seadec" "locf"
#> [1001] "stl" "auto.arima" "StructTS" "linear_i"
#> [1005] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [1009] "exponential_ma" "seadec" "locf" "stl"
#> [1013] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [1017] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [1021] "seadec" "locf" "stl" "auto.arima"
#> [1025] "StructTS" "linear_i" "spline_i" "stine_i"
#> [1029] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [1033] "locf" "stl" "auto.arima" "StructTS"
#> [1037] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [1041] "linear_ma" "exponential_ma" "seadec" "locf"
#> [1045] "stl" "auto.arima" "StructTS" "linear_i"
#> [1049] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [1053] "exponential_ma" "seadec" "locf" "stl"
#> [1057] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [1061] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [1065] "seadec" "locf" "stl" "auto.arima"
#> [1069] "StructTS" "linear_i" "spline_i" "stine_i"
#> [1073] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [1077] "locf" "stl" "auto.arima" "StructTS"
#> [1081] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [1085] "linear_ma" "exponential_ma" "seadec" "locf"
#> [1089] "stl" "auto.arima" "StructTS" "linear_i"
#> [1093] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [1097] "exponential_ma" "seadec" "locf" "stl"
#> [1101] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [1105] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [1109] "seadec" "locf" "stl" "auto.arima"
#> [1113] "StructTS" "linear_i" "spline_i" "stine_i"
#> [1117] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [1121] "locf" "stl" "auto.arima" "StructTS"
#> [1125] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [1129] "linear_ma" "exponential_ma" "seadec" "locf"
#> [1133] "stl" "auto.arima" "StructTS" "linear_i"
#> [1137] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [1141] "exponential_ma" "seadec" "locf" "stl"
#> [1145] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [1149] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [1153] "seadec" "locf" "stl" "auto.arima"
#> [1157] "StructTS" "linear_i" "spline_i" "stine_i"
#> [1161] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [1165] "locf" "stl" "auto.arima" "StructTS"
#> [1169] "linear_i" "spline_i" "stine_i" "simple_ma"
#> [1173] "linear_ma" "exponential_ma" "seadec" "locf"
#> [1177] "stl" "auto.arima" "StructTS" "linear_i"
#> [1181] "spline_i" "stine_i" "simple_ma" "linear_ma"
#> [1185] "exponential_ma" "seadec" "locf" "stl"
#> [1189] "auto.arima" "StructTS" "linear_i" "spline_i"
#> [1193] "stine_i" "simple_ma" "linear_ma" "exponential_ma"
#> [1197] "seadec" "locf" "stl" "auto.arima"
#> [1201] "StructTS" "linear_i" "spline_i" "stine_i"
#> [1205] "simple_ma" "linear_ma" "exponential_ma" "seadec"
#> [1209] "locf" "stl"
#>
#> $percent_md
#> [1] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [8] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [15] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [22] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [29] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [36] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [43] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [50] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [57] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [64] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [71] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [78] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [85] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [92] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [99] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [106] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [113] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [120] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [127] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [134] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [141] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [148] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [155] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [162] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [169] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [176] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [183] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [190] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [197] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [204] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [211] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [218] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [225] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [232] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [239] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [246] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [253] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [260] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [267] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [274] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [281] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [288] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [295] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [302] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [309] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [316] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [323] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [330] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [337] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [344] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [351] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [358] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [365] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [372] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [379] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [386] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [393] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [400] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [407] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [414] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [421] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [428] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [435] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [442] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [449] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [456] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [463] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [470] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [477] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [484] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [491] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [498] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [505] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [512] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [519] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [526] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [533] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [540] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [547] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [554] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [561] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [568] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [575] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [582] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [589] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [596] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [603] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [610] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [617] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [624] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [631] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [638] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [645] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [652] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [659] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [666] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [673] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [680] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [687] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [694] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [701] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [708] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [715] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [722] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [729] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [736] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [743] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [750] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [757] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [764] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [771] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [778] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [785] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [792] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [799] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [806] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [813] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [820] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [827] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [834] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [841] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [848] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [855] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [862] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [869] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [876] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [883] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [890] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [897] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [904] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [911] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [918] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [925] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [932] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [939] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [946] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [953] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [960] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [967] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [974] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [981] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [988] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [995] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1002] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1009] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1016] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1023] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1030] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1037] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1044] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1051] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1058] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1065] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1072] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1079] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1086] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1093] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1100] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1107] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1114] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1121] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1128] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1135] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1142] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1149] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1156] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1163] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1170] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1177] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1184] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1191] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1198] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [1205] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#>
#> $rmse
#> [1] 14.05045 13.26078 13.26078 17.46070 12.79776 17.38666 15.76341
#> [8] 14.69970 13.26078 24.44539 13.26078 12.23557 12.41317 12.41317
#> [15] 13.01043 12.36948 16.25045 15.22911 14.56711 12.41317 18.80415
#> [22] 12.41317 13.68033 13.62518 13.62518 14.37310 13.43526 18.07289
#> [29] 16.36159 15.25456 13.62518 22.24499 13.62518 13.51630 13.54310
#> [36] 13.54310 14.18836 13.35660 17.44570 15.89755 14.84470 13.54310
#> [43] 26.28794 13.54310 14.49103 14.68414 14.68414 14.43173 14.36652
#> [50] 17.86777 16.31030 15.20125 14.68414 25.13821 14.68414 17.56464
#> [57] 12.52344 12.52344 15.07084 12.14587 16.07550 14.66767 13.77509
#> [64] 12.52344 15.84165 12.52344 18.95263 18.45104 18.45104 21.50884
#> [71] 19.16696 20.95326 20.21137 19.90514 18.45104 33.23956 18.45104
#> [78] 18.51953 18.15947 18.15947 20.63667 19.85804 25.36308 24.42791
#> [85] 24.05594 18.15947 30.15453 18.15947 13.65127 11.88619 11.88619
#> [92] 14.54728 11.50398 17.06244 15.39275 14.11937 11.88619 22.78777
#> [99] 11.88619 13.75520 13.92680 13.92680 14.01799 13.51692 18.44760
#> [106] 16.95159 15.89943 13.92680 19.20502 13.92680 29.24626 13.16693
#> [113] 13.16693 17.07738 12.66064 17.46070 15.83604 14.75726 13.16693
#> [120] 23.93776 13.16693 12.00220 12.14597 12.14597 12.30524 11.64403
#> [127] 16.13772 15.10236 14.40624 12.14597 17.57150 12.14597 13.94336
#> [134] 13.88762 13.88762 14.35673 13.67704 18.12839 16.51746 15.48559
#> [141] 13.88762 22.10437 13.88762 13.69045 13.71472 13.71472 13.66190
#> [148] 13.47197 17.61452 16.14134 15.12489 13.71472 25.86899 13.71472
#> [155] 14.53868 14.72881 14.72881 14.43699 14.37028 17.83165 16.30693
#> [162] 15.21749 14.72881 24.67727 14.72881 18.33515 12.58861 12.58861
#> [169] 14.77224 12.20866 16.18820 14.80248 13.92196 12.58861 15.51486
#> [176] 12.58861 18.46299 18.53464 18.53464 21.86942 19.20607 20.72467
#> [183] 20.04059 19.79891 18.53464 33.32532 18.53464 18.80029 18.34183
#> [190] 18.34183 20.72343 20.03207 25.36212 24.48605 24.14980 18.34183
#> [197] 30.00934 18.34183 13.77719 12.02768 12.02768 14.17408 11.60859
#> [204] 17.15252 15.54869 14.31843 12.02768 22.52124 12.02768 13.65518
#> [211] 14.00630 14.00630 13.77703 13.58298 18.48375 17.04826 16.03489
#> [218] 14.00630 19.12958 14.00630 29.08513 12.37066 12.37066 16.29402
#> [225] 11.59951 16.92258 15.24981 14.12512 12.37066 23.29809 12.37066
#> [232] 12.00105 12.11009 12.11009 11.86719 11.26300 16.09545 15.11841
#> [239] 14.44753 12.11009 16.20696 12.11009 13.95270 14.24413 14.24413
#> [246] 14.38890 14.08382 18.27239 16.75331 15.77818 14.24413 21.96467
#> [253] 14.24413 13.19519 13.76803 13.76803 13.14571 13.50649 17.68558
#> [260] 16.27175 15.27915 13.76803 25.67978 13.76803 16.39494 14.65797
#> [267] 14.65797 14.18388 14.30428 17.85208 16.33920 15.23039 14.65797
#> [274] 24.21561 14.65797 18.10558 12.66407 12.66407 14.37508 12.29549
#> [281] 16.16741 14.81292 13.95465 12.66407 14.85140 12.66407 20.81067
#> [288] 18.51229 18.51229 21.60487 19.25370 21.01255 20.27896 19.97091
#> [295] 18.51229 32.78165 18.51229 18.88258 18.38269 18.38269 20.67593
#> [302] 20.08558 25.31938 24.49702 24.18275 18.38269 29.44202 18.38269
#> [309] 13.99932 12.28040 12.28040 14.12509 11.82123 17.35038 15.83380
#> [316] 14.64640 12.28040 22.25478 12.28040 13.57663 13.96350 13.96350
#> [323] 13.48089 13.51668 18.40914 16.98776 15.96427 13.96350 18.70046
#> [330] 13.96350 28.51853 12.28840 12.28840 16.08358 11.59777 17.25617
#> [337] 15.48029 14.28520 12.28840 24.16463 12.28840 11.99174 12.13013
#> [344] 12.13013 11.57625 11.60256 16.23928 15.21591 14.52536 12.13013
#> [351] 17.63917 12.13013 13.48530 13.69578 13.69578 14.06464 13.54342
#> [358] 18.01853 16.37352 15.32489 13.69578 21.99131 13.69578 13.26191
#> [365] 13.29195 13.29195 12.81448 13.03406 17.42289 15.89174 14.83311
#> [372] 13.29195 25.87557 13.29195 14.45483 14.46755 14.46755 13.87151
#> [379] 14.09744 17.77051 16.20969 15.08326 14.46755 24.89960 14.46755
#> [386] 41.08792 12.16554 12.16554 14.20000 11.62973 16.01389 14.52658
#> [393] 13.57577 12.16554 15.25294 12.16554 18.26829 18.33975 18.33975
#> [400] 21.70787 19.02539 20.83369 20.07270 19.76000 18.33975 33.04072
#> [407] 18.33975 18.70728 18.00220 18.00220 20.33518 19.68110 25.19792
#> [414] 24.28727 23.92736 18.00220 29.79284 18.00220 13.42867 11.62762
#> [421] 11.62762 14.19133 11.08008 17.28961 15.59256 14.26976 11.62762
#> [428] 22.35475 11.62762 13.11632 13.68571 13.68571 13.11617 13.18731
#> [435] 18.49871 16.95815 15.85586 13.68571 18.91262 13.68571 28.93505
#> [442] 12.35089 12.35089 16.24676 11.66191 16.92636 15.24675 14.11756
#> [449] 12.35089 23.36233 12.35089 11.99237 12.10355 12.10355 11.82356
#> [456] 11.23373 16.10748 15.12612 14.45301 12.10355 16.27047 12.10355
#> [463] 13.88828 14.19221 14.19221 14.32399 14.03373 18.26239 16.72958
#> [470] 15.74569 14.19221 21.95118 14.19221 13.14997 13.73118 13.73118
#> [477] 13.12777 13.47390 17.65265 16.23337 15.23858 13.73118 25.69641
#> [484] 13.73118 16.26649 14.61687 14.61687 14.11976 14.25983 17.82992
#> [491] 16.31148 15.19909 14.61687 24.22087 14.61687 18.05084 12.61582
#> [498] 12.61582 14.32160 12.24349 16.15897 14.79191 13.92491 12.61582
#> [505] 14.85543 12.61582 20.95441 18.48278 18.48278 21.56884 19.21400
#> [512] 21.00746 20.26735 19.95463 18.48278 32.77437 18.48278 18.87561
#> [519] 18.35605 18.35605 20.64119 20.05778 25.31044 24.48355 24.16699
#> [526] 18.35605 29.43510 18.35605 13.89767 12.16459 12.16459 14.10186
#> [533] 11.68663 17.30906 15.77070 14.56668 12.16459 22.24226 12.16459
#> [540] 13.50229 13.91297 13.91297 13.38598 13.46998 18.40242 16.96894
#> [547] 15.93598 13.91297 18.70924 13.91297 31.52480 13.51332 13.25797
#> [554] 17.88249 12.90642 16.61227 15.18990 14.27301 13.51332 22.50715
#> [561] 13.25797 12.59069 12.70567 12.63487 14.93507 12.60903 15.79734
#> [568] 14.93988 14.36031 12.70567 13.66109 12.63487 16.50354 16.41800
#> [575] 16.40801 17.84299 16.51072 18.89937 17.81340 17.17720 16.41800
#> [582] 22.84355 16.40801 15.90395 15.96481 15.90122 16.12873 15.78300
#> [589] 18.50679 17.51507 16.84672 15.96481 26.09428 15.90122 15.89220
#> [596] 15.88405 15.88405 16.86139 15.69516 18.14623 16.86687 15.93998
#> [603] 15.88405 23.55267 15.88405 21.51945 14.76976 14.77889 16.79690
#> [610] 14.61119 16.73172 15.79423 15.25594 14.76976 15.78134 14.77889
#> [617] 19.33367 19.34696 19.37331 22.83220 20.08060 21.07863 20.54417
#> [624] 20.38961 19.34696 33.03938 19.37331 20.00337 19.87124 19.88053
#> [631] 22.76920 21.57645 25.60573 25.04675 24.91566 19.87124 29.66286
#> [638] 19.88053 54.31853 14.93931 14.62738 15.79051 14.42818 17.88223
#> [645] 16.83281 16.04214 14.93931 22.62803 14.62738 15.42437 15.38410
#> [652] 15.37616 15.66024 15.18536 18.54111 17.47888 16.73568 15.38410
#> [659] 19.19197 15.37616 30.85194 12.97169 12.90233 17.33380 12.48214
#> [666] 16.62378 15.12553 14.14236 12.97169 22.42633 12.90233 12.29000
#> [673] 12.37203 12.35170 13.88127 12.21895 15.80933 14.90879 14.29028
#> [680] 12.37203 13.98993 12.35170 15.80267 15.72333 15.72333 16.65229
#> [687] 15.71665 18.70550 17.49661 16.75904 15.72333 22.52338 15.72333
#> [694] 15.26100 15.26347 15.26347 15.09222 15.08397 18.27463 17.16760
#> [701] 16.40581 15.26347 25.89828 15.26347 15.47246 15.50432 15.50432
#> [708] 16.05407 15.31586 18.04566 16.69178 15.70540 15.50432 23.51805
#> [715] 15.50432 20.60569 14.09925 14.09925 15.81235 13.88368 16.57038
#> [722] 15.51128 14.87597 14.09925 15.36868 14.09925 19.34450 19.09749
#> [729] 19.09749 22.45227 19.79344 21.03537 20.44402 20.24693 19.09749
#> [736] 32.91130 19.09749 19.49705 19.39784 19.39784 22.04593 21.09245
#> [743] 25.50432 24.87090 24.68567 19.39784 29.52275 19.39784 53.47268
#> [750] 14.14277 13.98521 15.07269 13.74551 17.71437 16.54736 15.65202
#> [757] 14.14277 22.46439 13.98521 15.23815 14.92251 14.92251 14.90855
#> [764] 14.66539 18.46202 17.30328 16.48115 14.92251 18.97535 14.92251
#> [771] 30.34466 12.65589 12.65589 16.97320 12.14606 16.66368 15.10325
#> [778] 14.06681 12.65589 22.45952 12.65589 12.11867 12.19362 12.19362
#> [785] 13.14040 11.88025 15.84825 14.91843 14.27585 12.19362 14.43817
#> [792] 12.19362 15.26321 15.19381 15.19381 15.79085 15.10253 18.55129
#> [799] 17.24252 16.42498 15.19381 22.32707 15.19381 14.76126 14.76793
#> [806] 14.76793 14.36191 14.53478 18.09191 16.88772 16.04996 14.76793
#> [813] 25.79016 14.76793 15.14286 15.22228 15.22228 15.48209 15.02406
#> [820] 17.97544 16.56142 15.52871 15.22228 23.56823 15.22228 19.91443
#> [827] 13.56910 13.56910 15.12678 13.29711 16.44660 15.28374 14.56712
#> [834] 13.56910 15.13560 13.56910 19.40073 18.88752 18.88752 22.20147
#> [841] 19.57925 21.00416 20.36538 20.13365 18.88752 32.83135 18.88752
#> [848] 19.12681 19.03634 19.03634 21.55320 20.71604 25.43046 24.73600
#> [855] 24.50787 19.03634 29.45817 19.03634 52.83602 13.48630 13.47749
#> [862] 14.60100 13.17008 17.59727 16.33043 15.34781 13.48630 22.37154
#> [869] 13.47749 14.60275 14.56908 14.56908 14.37609 14.26144 18.41542
#> [876] 17.17142 16.28121 14.56908 18.84461 14.56908 13.97040 13.17937
#> [883] 13.17937 16.68749 12.69683 17.61305 15.98466 14.89985 13.17937
#> [890] 24.48224 13.17937 12.17663 12.31866 12.31866 12.31045 11.99782
#> [897] 16.30701 15.27923 14.58884 12.31866 17.87790 12.31866 13.56083
#> [904] 13.69835 13.69835 14.22850 13.49598 18.10909 16.43366 15.35270
#> [911] 13.69835 22.09817 13.69835 13.17649 13.53572 13.53572 13.48010
#> [918] 13.31880 17.41977 15.92989 14.91266 13.53572 25.89704 13.53572
#> [925] 131.68857 14.71042 14.71042 14.26370 14.34659 17.94109 16.38496
#> [932] 15.26613 14.71042 25.00317 14.71042 18.34911 12.20703 12.20703
#> [939] 14.39564 11.83632 15.97875 14.52336 13.59211 12.20703 15.49746
#> [946] 12.20703 20.67433 18.46736 18.46736 21.91289 19.13131 20.70456
#> [953] 19.99844 19.74205 18.46736 33.24171 18.46736 18.84867 18.25167
#> [960] 18.25167 20.76330 19.95426 25.37059 24.45753 24.09178 18.25167
#> [967] 29.76522 18.25167 13.64643 11.88294 11.88294 14.11859 11.45158
#> [974] 17.21506 15.55687 14.28126 11.88294 22.53643 11.88294 13.39715
#> [981] 13.81115 13.81115 13.46409 13.35447 18.49826 17.00087 15.93417
#> [988] 13.81115 19.11903 13.81115 56.36292 13.50493 13.50493 16.72545
#> [995] 13.25860 17.89773 16.23101 15.16353 13.50493 27.21244 13.50493
#> [1002] 13.80091 13.97985 13.97985 15.39257 14.02221 16.86611 16.03890
#> [1009] 15.54053 13.97985 21.89100 13.97985 14.80333 14.73458 14.73458
#> [1016] 16.42218 14.84106 18.36811 16.83911 15.88359 14.73458 24.90276
#> [1023] 14.73458 51.79038 14.14421 14.14421 15.15583 14.11470 17.67956
#> [1030] 16.18080 15.17753 14.14421 28.22725 14.14421 15.08282 15.07635
#> [1037] 15.07635 15.79290 14.95788 17.88048 16.31228 15.23023 15.07635
#> [1044] 27.67481 15.07635 19.33531 13.55464 13.55464 14.84490 13.38460
#> [1051] 16.16786 14.89528 14.10760 13.55464 20.56499 13.55464 45.21239
#> [1058] 19.14420 19.14420 22.70968 19.94745 21.21033 20.53079 20.26941
#> [1065] 19.14420 35.35428 19.14420 19.60880 18.95166 18.95166 22.40097
#> [1072] 20.67497 25.61835 24.73200 24.38133 18.95166 31.34124 18.95166
#> [1079] 13.87383 12.22134 12.22134 13.48837 11.95399 17.44935 15.75137
#> [1086] 14.44249 12.22134 24.08399 12.22134 14.62213 14.56587 14.56587
#> [1093] 15.14051 14.27475 18.72619 17.24612 16.21190 14.56587 21.83730
#> [1100] 14.56587 14.00382 13.21107 13.21107 16.75287 12.63066 17.76589
#> [1107] 16.13142 15.04493 13.21107 24.84183 13.21107 12.44872 12.59522
#> [1114] 12.59522 13.13673 12.61746 16.32643 15.33057 14.68283 12.59522
#> [1121] 18.42946 12.59522 14.12693 13.67427 13.67427 14.44258 13.47879
#> [1128] 17.89182 16.23412 15.17440 13.67427 21.90489 13.67427 13.55713
#> [1135] 13.59315 13.59315 13.80139 13.49453 17.50507 15.97306 14.94000
#> [1142] 13.59315 25.92435 13.59315 14.94648 14.96144 14.96144 14.74437
#> [1149] 14.70506 17.95277 16.43290 15.36206 14.96144 25.34006 14.96144
#> [1156] 40.98095 12.45708 12.45708 14.89147 12.14218 16.04001 14.61806
#> [1163] 13.73218 12.45708 15.66885 12.45708 18.42125 18.49435 18.49435
#> [1170] 22.03189 19.24141 20.69922 19.98940 19.73982 18.49435 33.49188
#> [1177] 18.49435 18.76455 18.22207 18.22207 20.60254 19.96782 25.39398
#> [1184] 24.47445 24.10781 18.22207 29.96833 18.22207 13.94824 12.23804
#> [1191] 12.23804 15.02005 11.89572 17.25485 15.66233 14.45862 12.23804
#> [1198] 22.61250 12.23804 13.73717 13.89623 13.89623 13.88981 13.49120
#> [1205] 18.30312 16.84714 15.84089 13.89623 19.20398 13.89623
#>
#> $cor
#> [1] 0.9862110 0.9877469 0.9877469 0.9787401 0.9885842 0.9789472 0.9826987
#> [8] 0.9849501 0.9877469 0.9597547 0.9877469 0.9895579 0.9892599 0.9892599
#> [15] 0.9883102 0.9893327 0.9815702 0.9838173 0.9851995 0.9892599 0.9760303
#> [22] 0.9892599 0.9870289 0.9871150 0.9871150 0.9856006 0.9874697 0.9773955
#> [29] 0.9815066 0.9839176 0.9871150 0.9656584 0.9871150 0.9873425 0.9873099
#> [36] 0.9873099 0.9860269 0.9876621 0.9788978 0.9825107 0.9847676 0.9873099
#> [43] 0.9521268 0.9873099 0.9853467 0.9849427 0.9849427 0.9854884 0.9855905
#> [50] 0.9777121 0.9814238 0.9838633 0.9849427 0.9576172 0.9849427 0.9798297
#> [57] 0.9890532 0.9890532 0.9843531 0.9897039 0.9819875 0.9849977 0.9867569
#> [64] 0.9890532 0.9825336 0.9890532 0.9750836 0.9764333 0.9764333 0.9680978
#> [71] 0.9745170 0.9695893 0.9717265 0.9725763 0.9764333 0.9241565 0.9764333
#> [78] 0.9760764 0.9770245 0.9770245 0.9703645 0.9724798 0.9551598 0.9583861
#> [85] 0.9596365 0.9770245 0.9384529 0.9770245 0.9870137 0.9901496 0.9901496
#> [92] 0.9853985 0.9907733 0.9796917 0.9834809 0.9861042 0.9901496 0.9638603
#> [99] 0.9901496 0.9868599 0.9865457 0.9865457 0.9863590 0.9873579 0.9762613
#> [106] 0.9799757 0.9823970 0.9865457 0.9742437 0.9865457 0.9437335 0.9878668
#> [113] 0.9878668 0.9795443 0.9887803 0.9786610 0.9824521 0.9847571 0.9878668
#> [120] 0.9611124 0.9878668 0.9898940 0.9896554 0.9896554 0.9894441 0.9904814
#> [127] 0.9817287 0.9840000 0.9854451 0.9896554 0.9788851 0.9896554 0.9864681
#> [134] 0.9865591 0.9865591 0.9855901 0.9869660 0.9771410 0.9810563 0.9833430
#> [141] 0.9865591 0.9658917 0.9865591 0.9869586 0.9869291 0.9869291 0.9869925
#> [148] 0.9873937 0.9783818 0.9818811 0.9841100 0.9869291 0.9533957 0.9869291
#> [155] 0.9851722 0.9847686 0.9847686 0.9853945 0.9855046 0.9776796 0.9813297
#> [162] 0.9837400 0.9847686 0.9588297 0.9847686 0.9777831 0.9888733 0.9888733
#> [169] 0.9848148 0.9895357 0.9816412 0.9846440 0.9864048 0.9888733 0.9831360
#> [176] 0.9888733 0.9762370 0.9760727 0.9760727 0.9668423 0.9742609 0.9700918
#> [183] 0.9720501 0.9727137 0.9760727 0.9233491 0.9760727 0.9752289 0.9764655
#> [190] 0.9764655 0.9698950 0.9718588 0.9549156 0.9579602 0.9590991 0.9764655
#> [197] 0.9385313 0.9764655 0.9866909 0.9898712 0.9898712 0.9859768 0.9905660
#> [204] 0.9793722 0.9830619 0.9856419 0.9898712 0.9645061 0.9898712 0.9870119
#> [211] 0.9863310 0.9863310 0.9867757 0.9871758 0.9760369 0.9796365 0.9820003
#> [218] 0.9863310 0.9743054 0.9863310 0.9437895 0.9892373 0.9892373 0.9812707
#> [225] 0.9905525 0.9797800 0.9835925 0.9859218 0.9892373 0.9626169 0.9892373
#> [232] 0.9897935 0.9896119 0.9896119 0.9900525 0.9910059 0.9816488 0.9838119
#> [239] 0.9852202 0.9896119 0.9817499 0.9896119 0.9862815 0.9857265 0.9857265
#> [246] 0.9853916 0.9860508 0.9765602 0.9803269 0.9825435 0.9857265 0.9659657
#> [253] 0.9857265 0.9877774 0.9867127 0.9867127 0.9878729 0.9872245 0.9779994
#> [260] 0.9814116 0.9836304 0.9867127 0.9536666 0.9867127 0.9812096 0.9847744
#> [267] 0.9847744 0.9857626 0.9855034 0.9774167 0.9810801 0.9835602 0.9847744
#> [274] 0.9598746 0.9847744 0.9781095 0.9886300 0.9886300 0.9854498 0.9892832
#> [281] 0.9815229 0.9844831 0.9862157 0.9886300 0.9843984 0.9886300 0.9697043
#> [288] 0.9759511 0.9759511 0.9674675 0.9739500 0.9689800 0.9711289 0.9719991
#> [295] 0.9759511 0.9253705 0.9759511 0.9747579 0.9761296 0.9761296 0.9697440
#> [302] 0.9714326 0.9546227 0.9575062 0.9585822 0.9761296 0.9401523 0.9761296
#> [309] 0.9861277 0.9893476 0.9893476 0.9859066 0.9901414 0.9787002 0.9822731
#> [316] 0.9848375 0.9893476 0.9649917 0.9893476 0.9870158 0.9862705 0.9862705
#> [323] 0.9871992 0.9871651 0.9760008 0.9795837 0.9819832 0.9862705 0.9752063
#> [330] 0.9862705 0.9468286 0.9895432 0.9895432 0.9820484 0.9906992 0.9793179
#> [337] 0.9833646 0.9858312 0.9895432 0.9607532 0.9895432 0.9899854 0.9897606
#> [344] 0.9897606 0.9906989 0.9906190 0.9816340 0.9838804 0.9853164 0.9897606
#> [351] 0.9788914 0.9897606 0.9873541 0.9869968 0.9869968 0.9862351 0.9872855
#> [358] 0.9775730 0.9815076 0.9837887 0.9869968 0.9664803 0.9869968 0.9878726
#> [365] 0.9878349 0.9878349 0.9887054 0.9883122 0.9790145 0.9825787 0.9848434
#> [372] 0.9878349 0.9538080 0.9878349 0.9854373 0.9854094 0.9854094 0.9866019
#> [379] 0.9861480 0.9779923 0.9816850 0.9841411 0.9854094 0.9585523 0.9854094
#> [386] 0.8998448 0.9896910 0.9896910 0.9861281 0.9905770 0.9821538 0.9853096
#> [393] 0.9871598 0.9896910 0.9838515 0.9896910 0.9769554 0.9767962 0.9767962
#> [400] 0.9676878 0.9749862 0.9700274 0.9721984 0.9730573 0.9767962 0.9253946
#> [407] 0.9767962 0.9756193 0.9774691 0.9774691 0.9712303 0.9730144 0.9557971
#> [414] 0.9589192 0.9601224 0.9774691 0.9399231 0.9774691 0.9874441 0.9906082
#> [421] 0.9906082 0.9860709 0.9914823 0.9791886 0.9830874 0.9858426 0.9906082
#> [428] 0.9652818 0.9906082 0.9880682 0.9870102 0.9870102 0.9880652 0.9879603
#> [435] 0.9761545 0.9799757 0.9825047 0.9870102 0.9750716 0.9870102 0.9443146
#> [442] 0.9892734 0.9892734 0.9813755 0.9904534 0.9797695 0.9835986 0.9859367
#> [449] 0.9892734 0.9624182 0.9892734 0.9898066 0.9896217 0.9896217 0.9901230
#> [456] 0.9910511 0.9816183 0.9837927 0.9852066 0.9896217 0.9816073 0.9896217
#> [463] 0.9864021 0.9858262 0.9858262 0.9855144 0.9861452 0.9765825 0.9803799
#> [470] 0.9826126 0.9858262 0.9660009 0.9858262 0.9878604 0.9867838 0.9867838
#> [477] 0.9879072 0.9872864 0.9780818 0.9815002 0.9837182 0.9867838 0.9535933
#> [484] 0.9867838 0.9814866 0.9848565 0.9848565 0.9858883 0.9855904 0.9774685
#> [491] 0.9811407 0.9836246 0.9848565 0.9598631 0.9848565 0.9782568 0.9887146
#> [498] 0.9887146 0.9855566 0.9893718 0.9815395 0.9845250 0.9862724 0.9887146
#> [505] 0.9843886 0.9887146 0.9693003 0.9760274 0.9760274 0.9675720 0.9740540
#> [512] 0.9689939 0.9711615 0.9720443 0.9760274 0.9253933 0.9760274 0.9747720
#> [519] 0.9761953 0.9761953 0.9698417 0.9715072 0.9546477 0.9575461 0.9586292
#> [526] 0.9761953 0.9401772 0.9761953 0.9863249 0.9895477 0.9895477 0.9859543
#> [533] 0.9903647 0.9787995 0.9824131 0.9850017 0.9895477 0.9650270 0.9895477
#> [540] 0.9871570 0.9863688 0.9863688 0.9873800 0.9872540 0.9760145 0.9796260
#> [547] 0.9820446 0.9863688 0.9751789 0.9863688 0.9328165 0.9867906 0.9872867
#> [554] 0.9768140 0.9879579 0.9799655 0.9832662 0.9852232 0.9867906 0.9637366
#> [561] 0.9872867 0.9884491 0.9882287 0.9883607 0.9838288 0.9884105 0.9818046
#> [568] 0.9837257 0.9849631 0.9882287 0.9864725 0.9883607 0.9804073 0.9805835
#> [575] 0.9806062 0.9770549 0.9803863 0.9742592 0.9771692 0.9787699 0.9805835
#> [582] 0.9621127 0.9806062 0.9816713 0.9815477 0.9816928 0.9810933 0.9819791
#> [589] 0.9751809 0.9777924 0.9794658 0.9815477 0.9507002 0.9816928 0.9816508
#> [596] 0.9816540 0.9816540 0.9793441 0.9821005 0.9760281 0.9792960 0.9815146
#> [603] 0.9816540 0.9605947 0.9816540 0.9680263 0.9841208 0.9841000 0.9794577
#> [610] 0.9844688 0.9797188 0.9819178 0.9831074 0.9841208 0.9818486 0.9841000
#> [617] 0.9729106 0.9728994 0.9728253 0.9626676 0.9707861 0.9678339 0.9694518
#> [624] 0.9698988 0.9728994 0.9220415 0.9728253 0.9710585 0.9714224 0.9713883
#> [631] 0.9623168 0.9661611 0.9523120 0.9543528 0.9548148 0.9714224 0.9371175
#> [638] 0.9713883 0.8188654 0.9838091 0.9844796 0.9818422 0.9849107 0.9767923
#> [645] 0.9794440 0.9813305 0.9838091 0.9627818 0.9844796 0.9828776 0.9829488
#> [652] 0.9829667 0.9823265 0.9834250 0.9750311 0.9778443 0.9797109 0.9829488
#> [659] 0.9731593 0.9829667 0.9357911 0.9879066 0.9880366 0.9783454 0.9888177
#> [666] 0.9800493 0.9835003 0.9855747 0.9879066 0.9642420 0.9880366 0.9890511
#> [673] 0.9889013 0.9889379 0.9860954 0.9891758 0.9818820 0.9838871 0.9851960
#> [680] 0.9889013 0.9859293 0.9889379 0.9821171 0.9822740 0.9822740 0.9800987
#> [687] 0.9823120 0.9749160 0.9780895 0.9798958 0.9822740 0.9633739 0.9822740
#> [694] 0.9832371 0.9832460 0.9832460 0.9835631 0.9836540 0.9759471 0.9787995
#> [701] 0.9806531 0.9832460 0.9517238 0.9832460 0.9826949 0.9826098 0.9826098
#> [708] 0.9813749 0.9830439 0.9764182 0.9798287 0.9821463 0.9826098 0.9609636
#> [715] 0.9826098 0.9708603 0.9856017 0.9856017 0.9819028 0.9860458 0.9802022
#> [722] 0.9826442 0.9840177 0.9856017 0.9828821 0.9856017 0.9730583 0.9737623
#> [729] 0.9737623 0.9641003 0.9717940 0.9681609 0.9699366 0.9705050 0.9737623
#> [736] 0.9230699 0.9737623 0.9726299 0.9728863 0.9728863 0.9648422 0.9678222
#> [743] 0.9529433 0.9552331 0.9558843 0.9728863 0.9381660 0.9728863 0.8247718
#> [750] 0.9855666 0.9858870 0.9835344 0.9863769 0.9773360 0.9802336 0.9823177
#> [757] 0.9855666 0.9635191 0.9858870 0.9833301 0.9840338 0.9840338 0.9840639
#> [764] 0.9846172 0.9753647 0.9783920 0.9804182 0.9840338 0.9739032 0.9840338
#> [771] 0.9380930 0.9885610 0.9885610 0.9793638 0.9894863 0.9800667 0.9836417
#> [778] 0.9858097 0.9885610 0.9643868 0.9885610 0.9894134 0.9892818 0.9892818
#> [785] 0.9876024 0.9898256 0.9818998 0.9839618 0.9853141 0.9892818 0.9851410
#> [792] 0.9892818 0.9833945 0.9835259 0.9835259 0.9821757 0.9837438 0.9754593
#> [799] 0.9788347 0.9807910 0.9835259 0.9642189 0.9835259 0.9844205 0.9844205
#> [806] 0.9844205 0.9852214 0.9849249 0.9765691 0.9796139 0.9816026 0.9844205
#> [813] 0.9524121 0.9844205 0.9835118 0.9833253 0.9833253 0.9827738 0.9837732
#> [820] 0.9767294 0.9802494 0.9826385 0.9833253 0.9610597 0.9833253 0.9729698
#> [827] 0.9867342 0.9867342 0.9835482 0.9872680 0.9805934 0.9832342 0.9847526
#> [834] 0.9867342 0.9834945 0.9867342 0.9730855 0.9745009 0.9745009 0.9651041
#> [841] 0.9725751 0.9684495 0.9703531 0.9710177 0.9745009 0.9238742 0.9745009
#> [848] 0.9737847 0.9740141 0.9740141 0.9665740 0.9691201 0.9534736 0.9559620
#> [855] 0.9567592 0.9740141 0.9388760 0.9740141 0.8294449 0.9869473 0.9869644
#> [862] 0.9846342 0.9875620 0.9777481 0.9808479 0.9830879 0.9869473 0.9640246
#> [869] 0.9869644 0.9847970 0.9848552 0.9848552 0.9852535 0.9855308 0.9756138
#> [876] 0.9788270 0.9809861 0.9848552 0.9744047 0.9848552 0.9863830 0.9879253
#> [883] 0.9879253 0.9805920 0.9887901 0.9784302 0.9822390 0.9845642 0.9879253
#> [890] 0.9597304 0.9879253 0.9896647 0.9894283 0.9894283 0.9894943 0.9899622
#> [897] 0.9814631 0.9837291 0.9851714 0.9894283 0.9783218 0.9894283 0.9872333
#> [904] 0.9869887 0.9869887 0.9859130 0.9873731 0.9773036 0.9813407 0.9837087
#> [911] 0.9869887 0.9661096 0.9869887 0.9879956 0.9873616 0.9873616 0.9874475
#> [918] 0.9877742 0.9789951 0.9824701 0.9846572 0.9873616 0.9536423 0.9873616
#> [925] 0.4080538 0.9848998 0.9848998 0.9858240 0.9856386 0.9775448 0.9812671
#> [932] 0.9837373 0.9848998 0.9581546 0.9848998 0.9779496 0.9896045 0.9896045
#> [939] 0.9856763 0.9902267 0.9822172 0.9853045 0.9871185 0.9896045 0.9833036
#> [946] 0.9896045 0.9704891 0.9764101 0.9764101 0.9669924 0.9746501 0.9703420
#> [953] 0.9723481 0.9730487 0.9764101 0.9243396 0.9764101 0.9752495 0.9768330
#> [960] 0.9768330 0.9699824 0.9722490 0.9551619 0.9583169 0.9595496 0.9768330
#> [967] 0.9399001 0.9768330 0.9870274 0.9901700 0.9901700 0.9861827 0.9908723
#> [974] 0.9793404 0.9831393 0.9857960 0.9901700 0.9646791 0.9901700 0.9875599
#> [981] 0.9867737 0.9867737 0.9874301 0.9876568 0.9761362 0.9798611 0.9823216
#> [988] 0.9867737 0.9744977 0.9867737 0.8181861 0.9872397 0.9872397 0.9804865
#> [995] 0.9876927 0.9775593 0.9815498 0.9838906 0.9872397 0.9504424 0.9872397
#> [1002] 0.9866404 0.9862915 0.9862915 0.9834722 0.9862079 0.9800313 0.9819434
#> [1009] 0.9830517 0.9862915 0.9673107 0.9862915 0.9847670 0.9848812 0.9848812
#> [1016] 0.9810961 0.9846685 0.9766106 0.9803780 0.9825293 0.9848812 0.9567547
#> [1023] 0.9848812 0.8404097 0.9860844 0.9860844 0.9840308 0.9861531 0.9782131
#> [1030] 0.9817850 0.9839895 0.9860844 0.9447913 0.9860844 0.9840706 0.9840606
#> [1037] 0.9840606 0.9825809 0.9843153 0.9775848 0.9813385 0.9837300 0.9840606
#> [1044] 0.9491978 0.9840606 0.9754090 0.9871066 0.9871066 0.9846047 0.9874308
#> [1051] 0.9816974 0.9844599 0.9860486 0.9871066 0.9705301 0.9871066 0.8754496
#> [1058] 0.9744267 0.9744267 0.9640693 0.9721898 0.9686271 0.9706223 0.9713601
#> [1065] 0.9744267 0.9137511 0.9744267 0.9731885 0.9749943 0.9749943 0.9648775
#> [1072] 0.9700957 0.9540819 0.9571890 0.9583753 0.9749943 0.9324727 0.9749943
#> [1079] 0.9865271 0.9895613 0.9895613 0.9872959 0.9900196 0.9786985 0.9826587
#> [1086] 0.9854273 0.9895613 0.9594566 0.9895613 0.9851504 0.9852463 0.9852463
#> [1093] 0.9840298 0.9858390 0.9754261 0.9791849 0.9816277 0.9852463 0.9666129
#> [1100] 0.9852463 0.9864409 0.9879649 0.9879649 0.9806368 0.9890002 0.9782330
#> [1107] 0.9820545 0.9843858 0.9879649 0.9588571 0.9879649 0.9892996 0.9890517
#> [1114] 0.9890517 0.9881580 0.9890079 0.9815831 0.9837654 0.9851151 0.9890517
#> [1121] 0.9771753 0.9890517 0.9862117 0.9871335 0.9871335 0.9856028 0.9874941
#> [1128] 0.9780544 0.9819570 0.9842239 0.9871335 0.9670449 0.9871335 0.9873961
#> [1135] 0.9873468 0.9873468 0.9869384 0.9875321 0.9789577 0.9825108 0.9847169
#> [1142] 0.9873468 0.9540203 0.9873468 0.9845624 0.9845285 0.9845285 0.9850022
#> [1149] 0.9850577 0.9777290 0.9813353 0.9836882 0.9845285 0.9574180 0.9845285
#> [1156] 0.9010672 0.9892849 0.9892849 0.9848886 0.9898199 0.9822324 0.9852372
#> [1163] 0.9869639 0.9892849 0.9831242 0.9892849 0.9767150 0.9765511 0.9765511
#> [1170] 0.9668838 0.9745776 0.9706165 0.9726164 0.9732936 0.9765511 0.9238489
#> [1177] 0.9765511 0.9756975 0.9771119 0.9771119 0.9707214 0.9724623 0.9554923
#> [1184] 0.9586453 0.9598750 0.9771119 0.9397444 0.9771119 0.9865800 0.9896562
#> [1191] 0.9896562 0.9845575 0.9902277 0.9794282 0.9830563 0.9855624 0.9896562
#> [1198] 0.9647647 0.9896562 0.9870222 0.9867160 0.9867160 0.9867227 0.9874924
#> [1205] 0.9768501 0.9804016 0.9826822 0.9867160 0.9745188 0.9867160
#>
#> $mase
#> [1] 0.1520912 0.1450697 0.1450697 0.1821534 0.1423493 0.2052456 0.1830342
#> [8] 0.1714422 0.1450697 0.2660188 0.1450697 0.1211136 0.1227158 0.1227158
#> [15] 0.1278515 0.1229199 0.1813506 0.1641865 0.1528485 0.1227158 0.2293225
#> [22] 0.1227158 0.1236412 0.1228913 0.1228913 0.1265797 0.1212248 0.2131502
#> [29] 0.1827647 0.1607131 0.1228913 0.2197065 0.1228913 0.1294691 0.1298128
#> [36] 0.1298128 0.1455676 0.1264545 0.1987238 0.1740191 0.1571786 0.1298128
#> [43] 0.2493342 0.1298128 0.1456672 0.1506975 0.1506975 0.1418050 0.1478797
#> [50] 0.1966454 0.1779458 0.1661939 0.1506975 0.2609143 0.1506975 0.2178347
#> [57] 0.1307818 0.1307818 0.1524475 0.1272850 0.1908883 0.1695413 0.1550335
#> [64] 0.1307818 0.2050358 0.1307818 0.1679311 0.1664415 0.1664415 0.1787719
#> [71] 0.1645495 0.2430307 0.2215034 0.2074047 0.1664415 0.3071036 0.1664415
#> [78] 0.1605157 0.1647450 0.1647450 0.1604032 0.1684251 0.2604343 0.2375384
#> [85] 0.2253155 0.1647450 0.2919867 0.1647450 0.1500648 0.1363548 0.1363548
#> [92] 0.1863256 0.1281709 0.2097223 0.1862197 0.1677382 0.1363548 0.2477704
#> [99] 0.1363548 0.1317252 0.1359811 0.1359811 0.1253231 0.1340365 0.2132325
#> [106] 0.1897540 0.1721490 0.1359811 0.2190709 0.1359811 0.3361452 0.1474230
#> [113] 0.1474230 0.1822989 0.1434193 0.2129044 0.1902569 0.1773006 0.1474230
#> [120] 0.2638885 0.1474230 0.1206178 0.1220706 0.1220706 0.1223523 0.1177114
#> [127] 0.1875100 0.1689256 0.1564295 0.1220706 0.2222808 0.1220706 0.1282949
#> [134] 0.1278611 0.1278611 0.1269700 0.1255020 0.2205814 0.1906412 0.1686777
#> [141] 0.1278611 0.2221621 0.1278611 0.1346936 0.1354484 0.1354484 0.1400020
#> [148] 0.1291643 0.2076810 0.1835442 0.1673099 0.1354484 0.2460354 0.1354484
#> [155] 0.1480766 0.1516692 0.1516692 0.1430775 0.1481566 0.2028210 0.1825600
#> [162] 0.1694672 0.1516692 0.2588678 0.1516692 0.2271341 0.1326990 0.1326990
#> [169] 0.1520344 0.1282693 0.1981291 0.1760081 0.1603862 0.1326990 0.2055535
#> [176] 0.1326990 0.1728559 0.1728060 0.1728060 0.1837592 0.1703469 0.2477011
#> [183] 0.2263258 0.2123629 0.1728060 0.3167065 0.1728060 0.1688386 0.1731697
#> [190] 0.1731697 0.1689946 0.1784507 0.2696724 0.2469145 0.2347141 0.1731697
#> [197] 0.2974266 0.1731697 0.1538767 0.1402852 0.1402852 0.1860083 0.1310135
#> [204] 0.2172399 0.1948198 0.1768063 0.1402852 0.2478407 0.1402852 0.1317194
#> [211] 0.1404146 0.1404146 0.1265011 0.1375588 0.2191988 0.1962856 0.1786493
#> [218] 0.1404146 0.2228296 0.1404146 0.3463565 0.1401110 0.1401110 0.1775668
#> [225] 0.1310617 0.2192522 0.1942247 0.1803199 0.1401110 0.2672006 0.1401110
#> [232] 0.1316275 0.1333617 0.1333617 0.1219776 0.1219469 0.2005558 0.1820808
#> [239] 0.1702903 0.1333617 0.2231097 0.1333617 0.1407673 0.1413192 0.1413192
#> [246] 0.1382476 0.1393502 0.2381298 0.2087794 0.1871574 0.1413192 0.2390845
#> [253] 0.1413192 0.1341996 0.1447260 0.1447260 0.1336200 0.1375561 0.2218729
#> [260] 0.1984050 0.1827757 0.1447260 0.2539107 0.1447260 0.1888321 0.1598819
#> [267] 0.1598819 0.1495348 0.1537220 0.2184878 0.1966181 0.1822168 0.1598819
#> [274] 0.2690949 0.1598819 0.2466357 0.1436684 0.1436684 0.1524467 0.1385190
#> [281] 0.2128012 0.1900824 0.1737358 0.1436684 0.2087309 0.1436684 0.1903842
#> [288] 0.1815470 0.1815470 0.1940609 0.1780240 0.2655649 0.2422062 0.2267856
#> [295] 0.1815470 0.3197339 0.1815470 0.1775166 0.1821436 0.1821436 0.1793667
#> [302] 0.1855446 0.2864216 0.2629710 0.2499890 0.1821436 0.3053999 0.1821436
#> [309] 0.1692156 0.1547285 0.1547285 0.1942044 0.1439995 0.2349854 0.2132515
#> [316] 0.1960503 0.1547285 0.2584003 0.1547285 0.1390008 0.1486652 0.1486652
#> [323] 0.1311850 0.1423191 0.2368374 0.2117597 0.1923946 0.1486652 0.2265701
#> [330] 0.1486652 0.3329317 0.1384766 0.1384766 0.1677372 0.1322711 0.2198431
#> [337] 0.1940624 0.1788255 0.1384766 0.2773776 0.1384766 0.1264787 0.1285627
#> [344] 0.1285627 0.1104864 0.1222527 0.1964328 0.1773255 0.1652914 0.1285627
#> [351] 0.2329877 0.1285627 0.1285990 0.1314953 0.1314953 0.1249484 0.1317870
#> [358] 0.2320899 0.2014457 0.1788103 0.1314953 0.2320996 0.1314953 0.1353955
#> [365] 0.1363937 0.1363937 0.1217934 0.1302473 0.2150772 0.1906222 0.1744611
#> [372] 0.1363937 0.2538466 0.1363937 0.1553745 0.1557970 0.1557970 0.1334132
#> [379] 0.1499345 0.2139080 0.1922015 0.1771740 0.1557970 0.2740202 0.1557970
#> [386] 0.5469436 0.1355149 0.1355149 0.1469668 0.1274333 0.2096878 0.1853784
#> [393] 0.1671987 0.1355149 0.2102033 0.1355149 0.1761545 0.1761660 0.1761660
#> [400] 0.1836986 0.1734478 0.2607818 0.2369788 0.2214621 0.1761660 0.3205641
#> [407] 0.1761660 0.1659811 0.1735574 0.1735574 0.1628913 0.1763152 0.2815975
#> [414] 0.2561988 0.2421383 0.1735574 0.3024552 0.1735574 0.1557549 0.1415275
#> [421] 0.1415275 0.1918689 0.1301703 0.2298836 0.2049863 0.1850442 0.1415275
#> [428] 0.2551429 0.1415275 0.1267849 0.1435005 0.1435005 0.1182599 0.1384735
#> [435] 0.2351566 0.2090375 0.1896072 0.1435005 0.2254226 0.1435005 0.3435826
#> [442] 0.1397168 0.1397168 0.1754545 0.1325025 0.2195368 0.1943986 0.1803987
#> [449] 0.1397168 0.2683961 0.1397168 0.1310344 0.1326830 0.1326830 0.1205025
#> [456] 0.1208602 0.2004016 0.1818858 0.1700281 0.1326830 0.2236587 0.1326830
#> [463] 0.1391815 0.1399976 0.1399976 0.1355097 0.1383548 0.2379128 0.2081973
#> [470] 0.1863672 0.1399976 0.2384323 0.1399976 0.1331680 0.1437879 0.1437879
#> [477] 0.1327059 0.1368068 0.2212611 0.1976184 0.1819212 0.1437879 0.2545490
#> [484] 0.1437879 0.1863572 0.1581758 0.1581758 0.1469137 0.1520179 0.2179899
#> [491] 0.1959257 0.1814169 0.1581758 0.2686599 0.1581758 0.2460812 0.1420679
#> [498] 0.1420679 0.1507491 0.1368383 0.2130890 0.1901124 0.1734887 0.1420679
#> [505] 0.2087959 0.1420679 0.1892632 0.1800081 0.1800081 0.1922471 0.1759909
#> [512] 0.2652395 0.2417742 0.2260501 0.1800081 0.3194172 0.1800081 0.1763102
#> [519] 0.1812515 0.1812515 0.1782267 0.1844694 0.2863425 0.2627692 0.2495889
#> [526] 0.1812515 0.3047960 0.1812515 0.1665318 0.1520102 0.1520102 0.1939515
#> [533] 0.1407328 0.2343565 0.2118775 0.1943367 0.1520102 0.2577346 0.1520102
#> [540] 0.1363738 0.1469173 0.1469173 0.1273619 0.1407688 0.2366296 0.2112141
#> [547] 0.1916199 0.1469173 0.2269491 0.1469173 0.3632785 0.1533173 0.1511252
#> [554] 0.1948276 0.1495298 0.2003204 0.1804844 0.1689167 0.1533173 0.2331734
#> [561] 0.1511252 0.1367838 0.1414592 0.1379719 0.1643889 0.1398831 0.1882333
#> [568] 0.1724348 0.1622621 0.1414592 0.1826498 0.1379719 0.1608176 0.1601934
#> [575] 0.1597256 0.1854161 0.1643449 0.2299256 0.2069619 0.1906429 0.1601934
#> [582] 0.2390128 0.1597256 0.1626175 0.1647492 0.1633699 0.1699519 0.1615063
#> [589] 0.2159109 0.1986419 0.1882434 0.1647492 0.2480919 0.1633699 0.1753439
#> [596] 0.1752688 0.1752688 0.1910671 0.1729210 0.2102404 0.1929564 0.1803550
#> [603] 0.1752688 0.2405383 0.1752688 0.2750518 0.1587129 0.1581444 0.1789912
#> [610] 0.1573056 0.1991931 0.1828293 0.1723193 0.1587129 0.1983506 0.1581444
#> [617] 0.1884275 0.1889582 0.1885916 0.2138851 0.1874994 0.2486975 0.2296322
#> [624] 0.2173954 0.1889582 0.3063395 0.1885916 0.1947507 0.1948116 0.1936362
#> [631] 0.2131155 0.2020728 0.2682128 0.2533020 0.2458567 0.1948116 0.2922815
#> [638] 0.1936362 0.6980861 0.1790477 0.1727423 0.2030736 0.1683164 0.2269950
#> [645] 0.2124645 0.2006690 0.1790477 0.2515969 0.1727423 0.1583224 0.1579018
#> [652] 0.1577721 0.1649478 0.1592203 0.2195447 0.2001651 0.1850200 0.1579018
#> [659] 0.2189590 0.1577721 0.3663335 0.1501635 0.1494624 0.1909692 0.1463397
#> [666] 0.2070746 0.1850137 0.1723964 0.1501635 0.2362236 0.1494624 0.1364591
#> [673] 0.1385700 0.1376872 0.1567253 0.1382427 0.1940939 0.1773734 0.1659361
#> [680] 0.1385700 0.1915861 0.1376872 0.1577964 0.1568969 0.1568969 0.1738345
#> [687] 0.1606150 0.2344643 0.2095093 0.1917530 0.1568969 0.2391503 0.1568969
#> [694] 0.1602600 0.1609490 0.1609490 0.1622069 0.1574336 0.2208753 0.2017000
#> [701] 0.1896753 0.1609490 0.2506453 0.1609490 0.1727312 0.1745578 0.1745578
#> [708] 0.1853847 0.1717336 0.2153529 0.1964834 0.1826046 0.1745578 0.2454527
#> [715] 0.1745578 0.2732970 0.1574279 0.1574279 0.1707358 0.1556730 0.2050926
#> [722] 0.1871677 0.1750914 0.1574279 0.1991564 0.1574279 0.1921276 0.1900492
#> [729] 0.1900492 0.2118716 0.1880975 0.2564484 0.2359466 0.2227174 0.1900492
#> [736] 0.3120122 0.1900492 0.1945528 0.1933514 0.1933514 0.2072282 0.2006120
#> [743] 0.2764732 0.2592095 0.2501053 0.1933514 0.2980032 0.1933514 0.7048352
#> [750] 0.1740246 0.1709445 0.2021124 0.1653562 0.2328320 0.2164023 0.2029001
#> [757] 0.1740246 0.2540771 0.1709445 0.1634218 0.1578585 0.1578585 0.1588783
#> [764] 0.1572437 0.2262375 0.2050635 0.1885476 0.1578585 0.2210747 0.1578585
#> [771] 0.3652905 0.1464012 0.1464012 0.1863375 0.1415247 0.2112792 0.1880514
#> [778] 0.1745332 0.1464012 0.2426966 0.1464012 0.1349328 0.1364118 0.1364118
#> [785] 0.1487899 0.1342618 0.1972037 0.1797534 0.1675009 0.1364118 0.2006984
#> [792] 0.1364118 0.1535664 0.1529676 0.1529676 0.1628534 0.1547123 0.2362057
#> [799] 0.2099791 0.1912447 0.1529676 0.2398162 0.1529676 0.1567458 0.1574915
#> [806] 0.1574915 0.1538543 0.1521855 0.2226488 0.2019771 0.1886234 0.1574915
#> [813] 0.2518238 0.1574915 0.1686678 0.1719339 0.1719339 0.1789729 0.1690579
#> [820] 0.2173558 0.1974268 0.1825641 0.1719339 0.2506067 0.1719339 0.2691816
#> [827] 0.1546762 0.1546762 0.1631780 0.1519638 0.2081285 0.1887723 0.1754346
#> [834] 0.1546762 0.2012247 0.1546762 0.1925750 0.1890766 0.1890766 0.2090912
#> [841] 0.1867707 0.2604095 0.2387559 0.2248353 0.1890766 0.3140289 0.1890766
#> [848] 0.1920954 0.1909491 0.1909491 0.2012241 0.1965879 0.2806556 0.2614842
#> [855] 0.2509801 0.1909491 0.3014714 0.1909491 0.7036723 0.1678589 0.1676834
#> [862] 0.1994652 0.1600855 0.2353018 0.2173282 0.2025343 0.1678589 0.2552562
#> [869] 0.1676834 0.1562650 0.1559665 0.1559665 0.1518412 0.1539532 0.2299957
#> [876] 0.2075724 0.1901126 0.1559665 0.2229083 0.1559665 0.1574637 0.1503758
#> [883] 0.1503758 0.1799405 0.1469837 0.2171546 0.1940391 0.1815200 0.1503758
#> [890] 0.2737386 0.1503758 0.1245732 0.1259748 0.1259748 0.1237752 0.1246885
#> [897] 0.1899701 0.1720864 0.1599296 0.1259748 0.2254788 0.1259748 0.1237192
#> [904] 0.1251812 0.1251812 0.1260330 0.1230618 0.2223167 0.1918185 0.1690595
#> [911] 0.1251812 0.2237913 0.1251812 0.1267339 0.1346140 0.1346140 0.1375831
#> [918] 0.1289854 0.2067674 0.1823401 0.1657027 0.1346140 0.2498990 0.1346140
#> [925] 2.1577559 0.1543793 0.1543793 0.1411731 0.1490843 0.2056972 0.1847964
#> [932] 0.1714047 0.1543793 0.2657642 0.1543793 0.2264320 0.1290788 0.1290788
#> [939] 0.1454818 0.1245356 0.1975102 0.1745455 0.1591350 0.1290788 0.2060401
#> [946] 0.1290788 0.1773118 0.1733950 0.1733950 0.1841369 0.1697239 0.2511317
#> [953] 0.2291618 0.2148272 0.1733950 0.3181017 0.1733950 0.1691215 0.1725025
#> [960] 0.1725025 0.1717856 0.1781116 0.2711442 0.2483555 0.2359322 0.1725025
#> [967] 0.2983965 0.1725025 0.1545456 0.1406704 0.1406704 0.1844722 0.1312080
#> [974] 0.2190507 0.1955035 0.1769701 0.1406704 0.2500649 0.1406704 0.1277891
#> [981] 0.1380815 0.1380815 0.1230425 0.1340267 0.2216547 0.1974420 0.1790478
#> [988] 0.1380815 0.2247892 0.1380815 0.7733093 0.1628501 0.1628501 0.1899222
#> [995] 0.1613797 0.2290357 0.2049302 0.1915347 0.1628501 0.3275497 0.1628501
#> [1002] 0.1570118 0.1588974 0.1588974 0.1832722 0.1599781 0.2049095 0.1893677
#> [1009] 0.1796264 0.1588974 0.2880827 0.1588974 0.1513293 0.1498286 0.1498286
#> [1016] 0.1885788 0.1556170 0.2352123 0.2047319 0.1831181 0.1498286 0.2902305
#> [1023] 0.1498286 0.7185535 0.1535337 0.1535337 0.1783827 0.1531189 0.2192033
#> [1030] 0.1931008 0.1770115 0.1535337 0.2964057 0.1535337 0.1749358 0.1726199
#> [1037] 0.1726199 0.1891119 0.1712066 0.2201012 0.1984084 0.1844385 0.1726199
#> [1044] 0.3265653 0.1726199 0.2606644 0.1616568 0.1616568 0.1608876 0.1616483
#> [1051] 0.2146226 0.1921991 0.1762453 0.1616568 0.2756429 0.1616568 0.6218862
#> [1058] 0.1967088 0.1967088 0.2316215 0.1998629 0.2708117 0.2480741 0.2332946
#> [1065] 0.1967088 0.3757872 0.1967088 0.2058293 0.1963807 0.1963807 0.2351181
#> [1072] 0.2048029 0.2861332 0.2639805 0.2519975 0.1963807 0.3447327 0.1963807
#> [1079] 0.1688444 0.1551983 0.1551983 0.1895427 0.1489112 0.2373841 0.2110942
#> [1086] 0.1906308 0.1551983 0.2978376 0.1551983 0.1651138 0.1636108 0.1636108
#> [1093] 0.1674060 0.1637758 0.2375496 0.2124764 0.1937323 0.1636108 0.2702733
#> [1100] 0.1636108 0.1592036 0.1521344 0.1521344 0.1796529 0.1490535 0.2171326
#> [1107] 0.1943271 0.1818492 0.1521344 0.2807643 0.1521344 0.1278924 0.1291620
#> [1114] 0.1291620 0.1335204 0.1324014 0.1880456 0.1715409 0.1605483 0.1291620
#> [1121] 0.2310448 0.1291620 0.1329277 0.1276131 0.1276131 0.1290475 0.1262945
#> [1128] 0.2174197 0.1875294 0.1646331 0.1276131 0.2203125 0.1276131 0.1371181
#> [1135] 0.1379991 0.1379991 0.1458506 0.1357278 0.2046808 0.1806516 0.1646377
#> [1142] 0.1379991 0.2476965 0.1379991 0.1622514 0.1625789 0.1625789 0.1555275
#> [1149] 0.1608047 0.2038778 0.1848547 0.1729916 0.1625789 0.2749592 0.1625789
#> [1156] 0.5287391 0.1350112 0.1350112 0.1501063 0.1316771 0.1971819 0.1760885
#> [1163] 0.1612915 0.1350112 0.2102385 0.1350112 0.1752017 0.1752473 0.1752473
#> [1170] 0.1916896 0.1746717 0.2499269 0.2281578 0.2143970 0.1752473 0.3228492
#> [1177] 0.1752473 0.1707342 0.1741292 0.1741292 0.1709846 0.1823911 0.2687157
#> [1184] 0.2469657 0.2353610 0.1741292 0.2996513 0.1741292 0.1603171 0.1465474
#> [1191] 0.1465474 0.1947435 0.1398637 0.2151900 0.1933457 0.1763692 0.1465474
#> [1198] 0.2502277 0.1465474 0.1349995 0.1430905 0.1430905 0.1317716 0.1401649
#> [1205] 0.2163940 0.1936544 0.1761524 0.1430905 0.2262862 0.1430905
#>
#> $smape
#> [1] 0.01765882 0.01431906 0.01431906 0.01731104 0.01405481 0.01951093
#> [7] 0.01744626 0.01628225 0.01431906 0.02534790 0.01431906 0.01188814
#> [13] 0.01202410 0.01202410 0.01459715 0.01213399 0.01767295 0.01601607
#> [19] 0.01500033 0.01202410 0.02156707 0.01202410 0.01206969 0.01200398
#> [25] 0.01200398 0.01369507 0.01183963 0.02032089 0.01739183 0.01528942
#> [31] 0.01200398 0.01997699 0.01200398 0.01411229 0.01416875 0.01416875
#> [37] 0.01573368 0.01394529 0.02015330 0.01793473 0.01647836 0.01416875
#> [43] 0.02408349 0.01416875 0.01569219 0.01621027 0.01621027 0.01518404
#> [49] 0.01578555 0.02047133 0.01874043 0.01757701 0.01621027 0.02414597
#> [55] 0.01621027 0.02801870 0.01287774 0.01287774 0.01556395 0.01261040
#> [61] 0.01856514 0.01659151 0.01525553 0.01287774 0.01999622 0.01287774
#> [67] 0.01984402 0.01885267 0.01885267 0.02392471 0.01832323 0.02656472
#> [73] 0.02448788 0.02303819 0.01885267 0.02980738 0.01885267 0.01686785
#> [79] 0.01675270 0.01675270 0.01823164 0.01712339 0.02502236 0.02308174
#> [85] 0.02196073 0.01675270 0.02613356 0.01675270 0.01941978 0.01415804
#> [91] 0.01415804 0.01920273 0.01337367 0.02050942 0.01837459 0.01678222
#> [97] 0.01415804 0.02376252 0.01415804 0.01381493 0.01407944 0.01407944
#> [103] 0.01272544 0.01380319 0.02108749 0.01900936 0.01745711 0.01407944
#> [109] 0.02203179 0.01407944 0.04227355 0.01436964 0.01436964 0.01699998
#> [115] 0.01399839 0.01985849 0.01783451 0.01659736 0.01436964 0.02469510
#> [121] 0.01436964 0.01173612 0.01186143 0.01186143 0.01404291 0.01168809
#> [127] 0.01790599 0.01618318 0.01506091 0.01186143 0.02100844 0.01186143
#> [133] 0.01212516 0.01209503 0.01209503 0.01311548 0.01191335 0.02061869
#> [139] 0.01775740 0.01558638 0.01209503 0.01987830 0.01209503 0.01415457
#> [145] 0.01424244 0.01424244 0.01494488 0.01378135 0.02049267 0.01832973
#> [151] 0.01691422 0.01424244 0.02325687 0.01424244 0.01535401 0.01582062
#> [157] 0.01582062 0.01471920 0.01526667 0.02050762 0.01869553 0.01744512
#> [163] 0.01582062 0.02325706 0.01582062 0.02750114 0.01268652 0.01268652
#> [169] 0.01472941 0.01233372 0.01889199 0.01685802 0.01536546 0.01268652
#> [175] 0.01960558 0.01268652 0.01923439 0.01921809 0.01921809 0.02425927
#> [181] 0.01871847 0.02649519 0.02446488 0.02303845 0.01921809 0.03012902
#> [187] 0.01921809 0.01730212 0.01712166 0.01712166 0.01871926 0.01764368
#> [193] 0.02537034 0.02340588 0.02230034 0.01712166 0.02608863 0.01712166
#> [199] 0.01937342 0.01417364 0.01417364 0.01846975 0.01329242 0.02095235
#> [205] 0.01894503 0.01734671 0.01417364 0.02329588 0.01417364 0.01340726
#> [211] 0.01422191 0.01422191 0.01274619 0.01389448 0.02126909 0.01929210
#> [217] 0.01775567 0.01422191 0.02186987 0.01422191 0.04154401 0.01309202
#> [223] 0.01309202 0.01578632 0.01233502 0.01921895 0.01719621 0.01599160
#> [229] 0.01309202 0.02281817 0.01309202 0.01206560 0.01221554 0.01221554
#> [235] 0.01348368 0.01159551 0.01814617 0.01654025 0.01552622 0.01221554
#> [241] 0.01949232 0.01221554 0.01294118 0.01237823 0.01237823 0.01320743
#> [247] 0.01222460 0.02090172 0.01824617 0.01618451 0.01237823 0.01972963
#> [253] 0.01237823 0.01350867 0.01430481 0.01430481 0.01365340 0.01379721
#> [259] 0.02053516 0.01853244 0.01724352 0.01430481 0.02248917 0.01430481
#> [265] 0.01813340 0.01573041 0.01573041 0.01445973 0.01503737 0.02075129
#> [271] 0.01893907 0.01764916 0.01573041 0.02271856 0.01573041 0.02763004
#> [277] 0.01273802 0.01273802 0.01401077 0.01234258 0.01913433 0.01715800
#> [283] 0.01565865 0.01273802 0.01853127 0.01273802 0.02273855 0.01881398
#> [289] 0.01881398 0.02398853 0.01822641 0.02660962 0.02453882 0.02308019
#> [295] 0.01881398 0.02842525 0.01881398 0.01713675 0.01686422 0.01686422
#> [301] 0.01862702 0.01712321 0.02516821 0.02324923 0.02213870 0.01686422
#> [307] 0.02477359 0.01686422 0.01989707 0.01469634 0.01469634 0.01812952
#> [313] 0.01377477 0.02129229 0.01946987 0.01801574 0.01469634 0.02274492
#> [319] 0.01469634 0.01346325 0.01425435 0.01425435 0.01264539 0.01362529
#> [325] 0.02156888 0.01952996 0.01795046 0.01425435 0.02077373 0.01425435
#> [331] 0.04104889 0.01302810 0.01302810 0.01519472 0.01250723 0.01957153
#> [337] 0.01740374 0.01603618 0.01302810 0.02406119 0.01302810 0.01166378
#> [343] 0.01184369 0.01184369 0.01246412 0.01147940 0.01799071 0.01630710
#> [349] 0.01525610 0.01184369 0.02048374 0.01184369 0.01243825 0.01189461
#> [355] 0.01189461 0.01241699 0.01189501 0.02072068 0.01793446 0.01579215
#> [361] 0.01189461 0.01955684 0.01189461 0.01382606 0.01393069 0.01393069
#> [367] 0.01297177 0.01349024 0.02037572 0.01828317 0.01695476 0.01393069
#> [373] 0.02279434 0.01393069 0.01552550 0.01554675 0.01554675 0.01349237
#> [379] 0.01483461 0.02066948 0.01882115 0.01745669 0.01554675 0.02322051
#> [385] 0.01554675 0.07256267 0.01240474 0.01240474 0.01388248 0.01182283
#> [391] 0.01917061 0.01706990 0.01543741 0.01240474 0.01888202 0.01240474
#> [397] 0.01869017 0.01867650 0.01867650 0.02362209 0.01816357 0.02657244
#> [403] 0.02443408 0.02292543 0.01867650 0.02890260 0.01867650 0.01659516
#> [409] 0.01646337 0.01646337 0.01751347 0.01670003 0.02523020 0.02314972
#> [415] 0.02194124 0.01646337 0.02492686 0.01646337 0.01901037 0.01380796
#> [421] 0.01380796 0.01816364 0.01281943 0.02114995 0.01906740 0.01740350
#> [427] 0.01380796 0.02273123 0.01380796 0.01265134 0.01403625 0.01403625
#> [433] 0.01178710 0.01354397 0.02166843 0.01955345 0.01797205 0.01403625
#> [439] 0.02095058 0.01403625 0.04123272 0.01308747 0.01308747 0.01561174
#> [445] 0.01252869 0.01926577 0.01723274 0.01601926 0.01308747 0.02292308
#> [451] 0.01308747 0.01200890 0.01215375 0.01215375 0.01334058 0.01148961
#> [457] 0.01814339 0.01652933 0.01550628 0.01215375 0.01951466 0.01215375
#> [463] 0.01283794 0.01227264 0.01227264 0.01297569 0.01214390 0.02088833
#> [469] 0.01820217 0.01612534 0.01227264 0.01966379 0.01227264 0.01344145
#> [475] 0.01424224 0.01424224 0.01359333 0.01374876 0.02050503 0.01848662
#> [481] 0.01719265 0.01424224 0.02252656 0.01424224 0.01793973 0.01558615
#> [487] 0.01558615 0.01424467 0.01488403 0.02071858 0.01888743 0.01758687
#> [493] 0.01558615 0.02267379 0.01558615 0.02758538 0.01260450 0.01260450
#> [499] 0.01385777 0.01219838 0.01917340 0.01717734 0.01565410 0.01260450
#> [505] 0.01853725 0.01260450 0.02291555 0.01866934 0.01866934 0.02382616
#> [511] 0.01802698 0.02658632 0.02449929 0.02301179 0.01866934 0.02839757
#> [517] 0.01866934 0.01705415 0.01679521 0.01679521 0.01853977 0.01703841
#> [523] 0.02516951 0.02324172 0.02211419 0.01679521 0.02471821 0.01679521
#> [529] 0.01966883 0.01446640 0.01446640 0.01811169 0.01348997 0.02124951
#> [535] 0.01936558 0.01788068 0.01446640 0.02267365 0.01446640 0.01322367
#> [541] 0.01409827 0.01409827 0.01230219 0.01348726 0.02154859 0.01948096
#> [547] 0.01788344 0.01409827 0.02080720 0.01409827 0.04526340 0.01472265
#> [553] 0.01452442 0.01815161 0.01427142 0.01873941 0.01699416 0.01592231
#> [559] 0.01472265 0.02166821 0.01452442 0.01313985 0.01366389 0.01327525
#> [565] 0.01746363 0.01361187 0.01813573 0.01666627 0.01576977 0.01366389
#> [571] 0.01794977 0.01327525 0.01448412 0.01443293 0.01439644 0.01748282
#> [577] 0.01477049 0.02141697 0.01908275 0.01729052 0.01443293 0.02088918
#> [583] 0.01439644 0.01623785 0.01645703 0.01633036 0.01683585 0.01617911
#> [589] 0.02109065 0.01945278 0.01851532 0.01645703 0.02335104 0.01633036
#> [595] 0.01772248 0.01775723 0.01775723 0.01839204 0.01732442 0.02126513
#> [601] 0.01967226 0.01848619 0.01775723 0.02239056 0.01775723 0.03114214
#> [607] 0.01448977 0.01441486 0.01668847 0.01435220 0.01901455 0.01740127
#> [613] 0.01625590 0.01448977 0.01894128 0.01441486 0.02041217 0.02040852
#> [619] 0.02034659 0.02678274 0.01999278 0.02657981 0.02475091 0.02349920
#> [625] 0.02040852 0.02906537 0.02034659 0.01856304 0.01859141 0.01847783
#> [631] 0.02180221 0.01913385 0.02507193 0.02370562 0.02295694 0.01859141
#> [637] 0.02551426 0.01847783 0.09021990 0.01751556 0.01694801 0.01981623
#> [643] 0.01644490 0.02184147 0.02047194 0.01937232 0.01751556 0.02373808
#> [649] 0.01694801 0.01582455 0.01582479 0.01580931 0.01604012 0.01577276
#> [655] 0.02151127 0.01981347 0.01846491 0.01582479 0.02153004 0.01580931
#> [661] 0.04429633 0.01412924 0.01406933 0.01739033 0.01371319 0.01878722
#> [667] 0.01693424 0.01581433 0.01412924 0.02136839 0.01406933 0.01280502
#> [673] 0.01302896 0.01293373 0.01646288 0.01318332 0.01813125 0.01662964
#> [679] 0.01565785 0.01302896 0.01812221 0.01293373 0.01389880 0.01382791
#> [685] 0.01382791 0.01620127 0.01410845 0.02121338 0.01878971 0.01692770
#> [691] 0.01382791 0.02033683 0.01382791 0.01570110 0.01577996 0.01577996
#> [697] 0.01591010 0.01552635 0.02095623 0.01921777 0.01817898 0.01577996
#> [703] 0.02295691 0.01577996 0.01700170 0.01725448 0.01725448 0.01747286
#> [709] 0.01680207 0.02111926 0.01945438 0.01820409 0.01725448 0.02209178
#> [715] 0.01725448 0.03022608 0.01401124 0.01401124 0.01569785 0.01387306
#> [721] 0.01898680 0.01730854 0.01607170 0.01401124 0.01849490 0.01401124
#> [727] 0.02061425 0.01997535 0.01997535 0.02608153 0.01955175 0.02655795
#> [733] 0.02466949 0.02336526 0.01997535 0.02872496 0.01997535 0.01813749
#> [739] 0.01804202 0.01804202 0.02092570 0.01861123 0.02506360 0.02355625
#> [745] 0.02270597 0.01804202 0.02519700 0.01804202 0.08848183 0.01664763
#> [751] 0.01637864 0.01923317 0.01579883 0.02172744 0.02024828 0.01904154
#> [757] 0.01664763 0.02326300 0.01637864 0.01592164 0.01539273 0.01539273
#> [763] 0.01513316 0.01520017 0.02146761 0.01967404 0.01825775 0.01539273
#> [769] 0.02109834 0.01539273 0.04366540 0.01369757 0.01369757 0.01681472
#> [775] 0.01322347 0.01886644 0.01695779 0.01578778 0.01369757 0.02153934
#> [781] 0.01369757 0.01254321 0.01268298 0.01268298 0.01569171 0.01274534
#> [787] 0.01814338 0.01660447 0.01558015 0.01268298 0.01847365 0.01268298
#> [793] 0.01342826 0.01337984 0.01337984 0.01524444 0.01351143 0.02108220
#> [799] 0.01859045 0.01667752 0.01337984 0.02011033 0.01337984 0.01528015
#> [805] 0.01535962 0.01535962 0.01517212 0.01498833 0.02084047 0.01901553
#> [811] 0.01788978 0.01535962 0.02273338 0.01535962 0.01643145 0.01683793
#> [817] 0.01683793 0.01677369 0.01637908 0.02099589 0.01928260 0.01797373
#> [823] 0.01683793 0.02206517 0.01683793 0.02957554 0.01366009 0.01366009
#> [829] 0.01499570 0.01344924 0.01898503 0.01723019 0.01592122 0.01366009
#> [835] 0.01834651 0.01366009 0.02080291 0.01966393 0.01966393 0.02561091
#> [841] 0.01919910 0.02655730 0.02460404 0.02325776 0.01966393 0.02848684
#> [847] 0.01966393 0.01777278 0.01768384 0.01768384 0.02033794 0.01814664
#> [853] 0.02506712 0.02343936 0.02249903 0.01768384 0.02504325 0.01768384
#> [859] 0.08723555 0.01593910 0.01592404 0.01880095 0.01520343 0.02163415
#> [865] 0.02005950 0.01877225 0.01593910 0.02299185 0.01592404 0.01503657
#> [871] 0.01503492 0.01503492 0.01439700 0.01472750 0.02146016 0.01959070
#> [877] 0.01812146 0.01503492 0.02091907 0.01503492 0.01781138 0.01450147
#> [883] 0.01450147 0.01687804 0.01418101 0.02004467 0.01800641 0.01681467
#> [889] 0.01450147 0.02515598 0.01450147 0.01182792 0.01195531 0.01195531
#> [895] 0.01413344 0.01203721 0.01791561 0.01626181 0.01518630 0.01195531
#> [901] 0.02098497 0.01195531 0.01219984 0.01173236 0.01173236 0.01305083
#> [907] 0.01158507 0.02061972 0.01773391 0.01554201 0.01173236 0.01963759
#> [913] 0.01173236 0.01362353 0.01418304 0.01418304 0.01482016 0.01382695
#> [919] 0.02027317 0.01811685 0.01669894 0.01418304 0.02345655 0.01418304
#> [925] 0.40170940 0.01596075 0.01596075 0.01464123 0.01530013 0.02062250
#> [931] 0.01877169 0.01749931 0.01596075 0.02361819 0.01596075 0.02772708
#> [937] 0.01231334 0.01231334 0.01436382 0.01199506 0.01870200 0.01663598
#> [943] 0.01520307 0.01231334 0.01939624 0.01231334 0.02185044 0.01929466
#> [949] 0.01929466 0.02441959 0.01868688 0.02678665 0.02475306 0.02332323
#> [955] 0.01929466 0.03046070 0.01929466 0.01742978 0.01706838 0.01706838
#> [961] 0.01893901 0.01756337 0.02532390 0.02340848 0.02232673 0.01706838
#> [967] 0.02628506 0.01706838 0.01933807 0.01411505 0.01411505 0.01822237
#> [973] 0.01324795 0.02086462 0.01879826 0.01719664 0.01411505 0.02329005
#> [979] 0.01411505 0.01310070 0.01399246 0.01399246 0.01251984 0.01356636
#> [985] 0.02131947 0.01927231 0.01767660 0.01399246 0.02201874 0.01399246
#> [991] 0.10268905 0.01449691 0.01449691 0.01666628 0.01427315 0.01968367
#> [997] 0.01771409 0.01654334 0.01449691 0.02694176 0.01449691 0.01363683
#> [1003] 0.01379945 0.01379945 0.01752673 0.01396692 0.01818741 0.01677244
#> [1009] 0.01593913 0.01379945 0.02366040 0.01379945 0.01326940 0.01315706
#> [1015] 0.01315706 0.01684143 0.01357267 0.02058295 0.01786630 0.01593709
#> [1021] 0.01315706 0.02323986 0.01315706 0.09238050 0.01475521 0.01475521
#> [1027] 0.01681756 0.01470706 0.02025965 0.01808261 0.01679719 0.01475521
#> [1033] 0.02512776 0.01475521 0.01670880 0.01670539 0.01670539 0.01727159
#> [1039] 0.01635105 0.02084717 0.01902554 0.01777823 0.01670539 0.02672015
#> [1045] 0.01670539 0.02973214 0.01421279 0.01421279 0.01506281 0.01425074
#> [1051] 0.01917260 0.01722175 0.01580528 0.01421279 0.02315871 0.01421279
#> [1057] 0.08043175 0.01976558 0.01976558 0.02663399 0.01962324 0.02684801
#> [1063] 0.02480327 0.02339243 0.01976558 0.03206954 0.01976558 0.01882778
#> [1069] 0.01780051 0.01780051 0.02228237 0.01841580 0.02502308 0.02326120
#> [1075] 0.02223519 0.01780051 0.02757793 0.01780051 0.01994416 0.01489498
#> [1081] 0.01489498 0.01812034 0.01429351 0.02131026 0.01921504 0.01763758
#> [1087] 0.01489498 0.02578817 0.01489498 0.01536096 0.01527024 0.01527024
#> [1093] 0.01505475 0.01521046 0.02145196 0.01949575 0.01798039 0.01527024
#> [1099] 0.02409776 0.01527024 0.01808580 0.01477077 0.01477077 0.01699073
#> [1105] 0.01454068 0.02011295 0.01809842 0.01691808 0.01477077 0.02620128
#> [1111] 0.01477077 0.01203178 0.01213278 0.01213278 0.01465074 0.01253486
#> [1117] 0.01769141 0.01613800 0.01517448 0.01213278 0.02150534 0.01213278
#> [1123] 0.01291653 0.01208562 0.01208562 0.01362014 0.01201706 0.02026513
#> [1129] 0.01740977 0.01524875 0.01208562 0.01968078 0.01208562 0.01437038
#> [1135] 0.01446541 0.01446541 0.01550088 0.01435609 0.02011170 0.01796209
#> [1141] 0.01659166 0.01446541 0.02350751 0.01446541 0.01692136 0.01693355
#> [1147] 0.01693355 0.01631016 0.01667661 0.02058877 0.01889094 0.01775166
#> [1153] 0.01693355 0.02514617 0.01693355 0.07383956 0.01309373 0.01309373
#> [1159] 0.01500994 0.01287229 0.01875080 0.01687501 0.01554174 0.01309373
#> [1165] 0.02037246 0.01309373 0.01951148 0.01950427 0.01950427 0.02510751
#> [1171] 0.01911562 0.02676470 0.02472394 0.02332078 0.01950427 0.03087568
#> [1177] 0.01950427 0.01760505 0.01726470 0.01726470 0.01885501 0.01795220
#> [1183] 0.02523872 0.02342112 0.02239477 0.01726470 0.02663514 0.01726470
#> [1189] 0.01988199 0.01464559 0.01464559 0.01959266 0.01403626 0.02046488
#> [1195] 0.01848478 0.01700734 0.01464559 0.02350836 0.01464559 0.01379801
#> [1201] 0.01454761 0.01454761 0.01340378 0.01420333 0.02102935 0.01911828
#> [1207] 0.01759383 0.01454761 0.02254563 0.01454761
#>
#> attr(,"row.names")
#> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14
#> [15] 15 16 17 18 19 20 21 22 23 24 25 26 27 28
#> [29] 29 30 31 32 33 34 35 36 37 38 39 40 41 42
#> [43] 43 44 45 46 47 48 49 50 51 52 53 54 55 56
#> [57] 57 58 59 60 61 62 63 64 65 66 67 68 69 70
#> [71] 71 72 73 74 75 76 77 78 79 80 81 82 83 84
#> [85] 85 86 87 88 89 90 91 92 93 94 95 96 97 98
#> [99] 99 100 101 102 103 104 105 106 107 108 109 110 111 112
#> [113] 113 114 115 116 117 118 119 120 121 122 123 124 125 126
#> [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140
#> [141] 141 142 143 144 145 146 147 148 149 150 151 152 153 154
#> [155] 155 156 157 158 159 160 161 162 163 164 165 166 167 168
#> [169] 169 170 171 172 173 174 175 176 177 178 179 180 181 182
#> [183] 183 184 185 186 187 188 189 190 191 192 193 194 195 196
#> [197] 197 198 199 200 201 202 203 204 205 206 207 208 209 210
#> [211] 211 212 213 214 215 216 217 218 219 220 221 222 223 224
#> [225] 225 226 227 228 229 230 231 232 233 234 235 236 237 238
#> [239] 239 240 241 242 243 244 245 246 247 248 249 250 251 252
#> [253] 253 254 255 256 257 258 259 260 261 262 263 264 265 266
#> [267] 267 268 269 270 271 272 273 274 275 276 277 278 279 280
#> [281] 281 282 283 284 285 286 287 288 289 290 291 292 293 294
#> [295] 295 296 297 298 299 300 301 302 303 304 305 306 307 308
#> [309] 309 310 311 312 313 314 315 316 317 318 319 320 321 322
#> [323] 323 324 325 326 327 328 329 330 331 332 333 334 335 336
#> [337] 337 338 339 340 341 342 343 344 345 346 347 348 349 350
#> [351] 351 352 353 354 355 356 357 358 359 360 361 362 363 364
#> [365] 365 366 367 368 369 370 371 372 373 374 375 376 377 378
#> [379] 379 380 381 382 383 384 385 386 387 388 389 390 391 392
#> [393] 393 394 395 396 397 398 399 400 401 402 403 404 405 406
#> [407] 407 408 409 410 411 412 413 414 415 416 417 418 419 420
#> [421] 421 422 423 424 425 426 427 428 429 430 431 432 433 434
#> [435] 435 436 437 438 439 440 441 442 443 444 445 446 447 448
#> [449] 449 450 451 452 453 454 455 456 457 458 459 460 461 462
#> [463] 463 464 465 466 467 468 469 470 471 472 473 474 475 476
#> [477] 477 478 479 480 481 482 483 484 485 486 487 488 489 490
#> [491] 491 492 493 494 495 496 497 498 499 500 501 502 503 504
#> [505] 505 506 507 508 509 510 511 512 513 514 515 516 517 518
#> [519] 519 520 521 522 523 524 525 526 527 528 529 530 531 532
#> [533] 533 534 535 536 537 538 539 540 541 542 543 544 545 546
#> [547] 547 548 549 550 551 552 553 554 555 556 557 558 559 560
#> [561] 561 562 563 564 565 566 567 568 569 570 571 572 573 574
#> [575] 575 576 577 578 579 580 581 582 583 584 585 586 587 588
#> [589] 589 590 591 592 593 594 595 596 597 598 599 600 601 602
#> [603] 603 604 605 606 607 608 609 610 611 612 613 614 615 616
#> [617] 617 618 619 620 621 622 623 624 625 626 627 628 629 630
#> [631] 631 632 633 634 635 636 637 638 639 640 641 642 643 644
#> [645] 645 646 647 648 649 650 651 652 653 654 655 656 657 658
#> [659] 659 660 661 662 663 664 665 666 667 668 669 670 671 672
#> [673] 673 674 675 676 677 678 679 680 681 682 683 684 685 686
#> [687] 687 688 689 690 691 692 693 694 695 696 697 698 699 700
#> [701] 701 702 703 704 705 706 707 708 709 710 711 712 713 714
#> [715] 715 716 717 718 719 720 721 722 723 724 725 726 727 728
#> [729] 729 730 731 732 733 734 735 736 737 738 739 740 741 742
#> [743] 743 744 745 746 747 748 749 750 751 752 753 754 755 756
#> [757] 757 758 759 760 761 762 763 764 765 766 767 768 769 770
#> [771] 771 772 773 774 775 776 777 778 779 780 781 782 783 784
#> [785] 785 786 787 788 789 790 791 792 793 794 795 796 797 798
#> [799] 799 800 801 802 803 804 805 806 807 808 809 810 811 812
#> [813] 813 814 815 816 817 818 819 820 821 822 823 824 825 826
#> [827] 827 828 829 830 831 832 833 834 835 836 837 838 839 840
#> [841] 841 842 843 844 845 846 847 848 849 850 851 852 853 854
#> [855] 855 856 857 858 859 860 861 862 863 864 865 866 867 868
#> [869] 869 870 871 872 873 874 875 876 877 878 879 880 881 882
#> [883] 883 884 885 886 887 888 889 890 891 892 893 894 895 896
#> [897] 897 898 899 900 901 902 903 904 905 906 907 908 909 910
#> [911] 911 912 913 914 915 916 917 918 919 920 921 922 923 924
#> [925] 925 926 927 928 929 930 931 932 933 934 935 936 937 938
#> [939] 939 940 941 942 943 944 945 946 947 948 949 950 951 952
#> [953] 953 954 955 956 957 958 959 960 961 962 963 964 965 966
#> [967] 967 968 969 970 971 972 973 974 975 976 977 978 979 980
#> [981] 981 982 983 984 985 986 987 988 989 990 991 992 993 994
#> [995] 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008
#> [1009] 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022
#> [1023] 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036
#> [1037] 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050
#> [1051] 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064
#> [1065] 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078
#> [1079] 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092
#> [1093] 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106
#> [1107] 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120
#> [1121] 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134
#> [1135] 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148
#> [1149] 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162
#> [1163] 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176
#> [1177] 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190
#> [1191] 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204
#> [1205] 1205 1206 1207 1208 1209 1210
#> attr(,"class")
#> [1] "kssa.table"
#>
#> [[2]]
#> $start_methods
#> [1] "StructTS" "StructTS" "StructTS" "StructTS"
#> [5] "StructTS" "StructTS" "StructTS" "StructTS"
#> [9] "StructTS" "StructTS" "StructTS" "auto.arima"
#> [13] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [17] "auto.arima" "auto.arima" "auto.arima" "auto.arima"
#> [21] "auto.arima" "auto.arima" "exponential_ma" "exponential_ma"
#> [25] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [29] "exponential_ma" "exponential_ma" "exponential_ma" "exponential_ma"
#> [33] "exponential_ma" "linear_i" "linear_i" "linear_i"
#> [37] "linear_i" "linear_i" "linear_i" "linear_i"
#> [41] "linear_i" "linear_i" "linear_i" "linear_i"
#> [45] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [49] "linear_ma" "linear_ma" "linear_ma" "linear_ma"
#> [53] "linear_ma" "linear_ma" "linear_ma" "locf"
#> [57] "locf" "locf" "locf" "locf"
#> [61] "locf" "locf" "locf" "locf"
#> [65] "locf" "locf" "seadec" "seadec"
#> [69] "seadec" "seadec" "seadec" "seadec"
#> [73] "seadec" "seadec" "seadec" "seadec"
#> [77] "seadec" "simple_ma" "simple_ma" "simple_ma"
#> [81] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [85] "simple_ma" "simple_ma" "simple_ma" "simple_ma"
#> [89] "spline_i" "spline_i" "spline_i" "spline_i"
#> [93] "spline_i" "spline_i" "spline_i" "spline_i"
#> [97] "spline_i" "spline_i" "spline_i" "stine_i"
#> [101] "stine_i" "stine_i" "stine_i" "stine_i"
#> [105] "stine_i" "stine_i" "stine_i" "stine_i"
#> [109] "stine_i" "stine_i" "stl" "stl"
#> [113] "stl" "stl" "stl" "stl"
#> [117] "stl" "stl" "stl" "stl"
#> [121] "stl"
#>
#> $actual_methods
#> [1] "StructTS" "auto.arima" "exponential_ma" "linear_i"
#> [5] "linear_ma" "locf" "seadec" "simple_ma"
#> [9] "spline_i" "stine_i" "stl" "StructTS"
#> [13] "auto.arima" "exponential_ma" "linear_i" "linear_ma"
#> [17] "locf" "seadec" "simple_ma" "spline_i"
#> [21] "stine_i" "stl" "StructTS" "auto.arima"
#> [25] "exponential_ma" "linear_i" "linear_ma" "locf"
#> [29] "seadec" "simple_ma" "spline_i" "stine_i"
#> [33] "stl" "StructTS" "auto.arima" "exponential_ma"
#> [37] "linear_i" "linear_ma" "locf" "seadec"
#> [41] "simple_ma" "spline_i" "stine_i" "stl"
#> [45] "StructTS" "auto.arima" "exponential_ma" "linear_i"
#> [49] "linear_ma" "locf" "seadec" "simple_ma"
#> [53] "spline_i" "stine_i" "stl" "StructTS"
#> [57] "auto.arima" "exponential_ma" "linear_i" "linear_ma"
#> [61] "locf" "seadec" "simple_ma" "spline_i"
#> [65] "stine_i" "stl" "StructTS" "auto.arima"
#> [69] "exponential_ma" "linear_i" "linear_ma" "locf"
#> [73] "seadec" "simple_ma" "spline_i" "stine_i"
#> [77] "stl" "StructTS" "auto.arima" "exponential_ma"
#> [81] "linear_i" "linear_ma" "locf" "seadec"
#> [85] "simple_ma" "spline_i" "stine_i" "stl"
#> [89] "StructTS" "auto.arima" "exponential_ma" "linear_i"
#> [93] "linear_ma" "locf" "seadec" "simple_ma"
#> [97] "spline_i" "stine_i" "stl" "StructTS"
#> [101] "auto.arima" "exponential_ma" "linear_i" "linear_ma"
#> [105] "locf" "seadec" "simple_ma" "spline_i"
#> [109] "stine_i" "stl" "StructTS" "auto.arima"
#> [113] "exponential_ma" "linear_i" "linear_ma" "locf"
#> [117] "seadec" "simple_ma" "spline_i" "stine_i"
#> [121] "stl"
#>
#> $mean_na
#> [1] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [8] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [15] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [22] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [29] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [36] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [43] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [50] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [57] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [64] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [71] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [78] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [85] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [92] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [99] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [106] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [113] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [120] 0.2008547 0.2008547
#>
#> $std_na
#> [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [38] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [75] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [112] 0 0 0 0 0 0 0 0 0 0
#>
#> $mean_rmse
#> [1] 14.31431 16.64517 16.32155 14.31431 17.18302 23.46602 14.31431 18.50842
#> [9] 15.71544 14.24623 14.31431 14.24733 15.04170 16.23223 14.24733 17.12133
#> [17] 23.81492 14.24733 18.49253 15.92459 14.25174 14.24733 14.95819 21.35114
#> [25] 16.71840 14.95731 17.46003 22.72244 14.95819 18.60245 16.36070 14.97116
#> [33] 14.95731 14.29538 17.00038 16.35793 14.29538 17.21429 22.93954 14.29538
#> [41] 18.50870 15.41416 14.17298 14.29538 15.34947 21.78361 16.92446 15.32475
#> [49] 17.60671 22.75984 15.34947 18.67454 16.93054 15.39980 15.32475 14.98776
#> [57] 26.44928 16.64081 14.98776 17.47576 26.30901 14.98776 18.78641 16.80734
#> [65] 15.14302 14.98776 14.20627 26.94886 16.26615 14.20627 17.15495 23.55184
#> [73] 14.20627 18.51572 15.56248 14.15840 14.20627 15.87972 22.30146 17.19363
#> [81] 15.81224 17.80220 22.89623 15.87972 18.78014 17.74997 15.93861 15.81224
#> [89] 13.96946 18.63208 16.14406 13.96946 17.06084 23.39241 13.96946 18.45412
#> [97] 15.19610 13.84789 13.96946 14.25269 16.95130 16.33031 14.25269 17.19297
#> [105] 22.95177 14.25269 18.49671 15.36613 14.13350 14.25269 14.33429 17.49353
#> [113] 16.30835 14.33429 17.16935 23.73861 14.33429 18.51331 15.93137 14.36648
#> [121] 14.33429
#>
#> $std_rmse
#> [1] 2.334887 5.041850 3.209211 2.334887 2.949485 5.446737 2.334887
#> [8] 2.733067 3.182524 2.978609 2.334887 2.286111 2.373105 3.238287
#> [15] 2.286111 2.983822 5.278160 2.286111 2.770099 2.946764 2.891613
#> [22] 2.286111 2.343390 12.169215 3.231488 2.344007 2.993934 5.766395
#> [29] 2.343390 2.790537 3.081698 2.953972 2.344007 2.362017 5.111857
#> [36] 3.241189 2.362017 2.986500 5.563269 2.362017 2.768712 3.224143
#> [43] 3.087952 2.362017 2.317293 12.247973 3.227462 2.337702 2.998164
#> [50] 5.824576 2.317293 2.800503 2.965222 2.908278 2.337702 2.282095
#> [57] 17.350254 3.207862 2.282095 2.957500 4.630079 2.282095 2.746657
#> [64] 3.156730 2.861450 2.282095 2.348817 36.916610 3.212293 2.348817
#> [71] 2.951794 5.383435 2.348817 2.734518 3.246703 2.975276 2.348817
#> [78] 2.267830 12.392108 3.221186 2.330524 3.000973 5.861232 2.267830
#> [85] 2.809086 2.818676 2.872149 2.330524 2.384498 9.288675 3.222101
#> [92] 2.384498 2.950460 5.431886 2.384498 2.718559 3.295435 3.069059
#> [99] 2.384498 2.369483 5.106202 3.246107 2.369483 2.989141 5.553011
#> [106] 2.369483 2.768906 3.229815 3.089166 2.369483 2.265570 8.509860
#> [113] 3.182862 2.265570 2.934615 5.385130 2.265570 2.726925 3.014101
#> [120] 2.880842 2.265570
#>
#> $mean_cor
#> [1] 0.9853393 0.9795178 0.9807255 0.9853393 0.9788072 0.9601942 0.9853393
#> [8] 0.9755650 0.9821270 0.9852523 0.9853393 0.9855581 0.9840350 0.9810169
#> [15] 0.9855581 0.9790524 0.9594434 0.9855581 0.9757212 0.9818739 0.9853471
#> [22] 0.9855581 0.9836166 0.9612915 0.9792759 0.9836183 0.9775526 0.9611892
#> [29] 0.9836166 0.9746603 0.9802251 0.9833810 0.9836183 0.9852392 0.9784567
#> [36] 0.9804494 0.9852392 0.9785198 0.9613993 0.9852392 0.9753232 0.9826118
#> [43] 0.9852309 0.9852392 0.9826788 0.9597542 0.9786609 0.9827275 0.9770545
#> [50] 0.9607773 0.9826788 0.9743220 0.9787921 0.9823660 0.9827275 0.9839893
#> [57] 0.9409798 0.9800030 0.9839893 0.9781110 0.9511320 0.9839893 0.9748530
#> [64] 0.9796544 0.9834612 0.9839893 0.9856395 0.9257606 0.9809673 0.9856395
#> [71] 0.9790016 0.9602679 0.9856395 0.9756935 0.9825535 0.9855193 0.9856395
#> [78] 0.9814005 0.9578733 0.9778799 0.9815360 0.9764260 0.9600566 0.9814005
#> [85] 0.9738926 0.9766746 0.9810586 0.9815360 0.9861119 0.9725410 0.9812608
#> [92] 0.9861119 0.9792507 0.9608008 0.9861119 0.9758853 0.9833472 0.9861084
#> [99] 0.9861119 0.9853215 0.9785681 0.9805091 0.9853215 0.9785684 0.9613648
#> [106] 0.9853215 0.9753516 0.9827113 0.9853078 0.9853215 0.9855345 0.9760993
#> [113] 0.9810507 0.9855345 0.9791580 0.9600516 0.9855345 0.9759177 0.9820112
#> [120] 0.9852672 0.9855345
#>
#> $std_cor
#> [1] 0.005033023 0.013595799 0.008536589 0.005033023 0.008125665 0.018262368
#> [7] 0.005033023 0.007961410 0.007698846 0.006648782 0.005033023 0.004884471
#> [13] 0.005108429 0.008515642 0.004884471 0.008138950 0.017726922 0.004884471
#> [19] 0.008008132 0.007121016 0.006425766 0.004884471 0.005322205 0.048549925
#> [25] 0.008949348 0.005323395 0.008524926 0.018975579 0.005322205 0.008321975
#> [31] 0.007896523 0.006982747 0.005323395 0.005125354 0.013778131 0.008700771
#> [37] 0.005125354 0.008292561 0.018198309 0.005125354 0.008110325 0.007727153
#> [43] 0.006898620 0.005125354 0.005381596 0.049724300 0.009059044 0.005420308
#> [49] 0.008628264 0.019249578 0.005381596 0.008413607 0.007853415 0.007056174
#> [55] 0.005420308 0.005118093 0.067982215 0.008638690 0.005118093 0.008242981
#> [61] 0.017538961 0.005118093 0.008083899 0.008221649 0.006708114 0.005118093
#> [67] 0.005002029 0.182018767 0.008457898 0.005002029 0.008063462 0.017848127
#> [73] 0.005002029 0.007915793 0.007780613 0.006570961 0.005002029 0.005414594
#> [79] 0.051265851 0.009182699 0.005544644 0.008742464 0.019518504 0.005414594
#> [85] 0.008510874 0.007794134 0.007176829 0.005544644 0.004996074 0.028602900
#> [91] 0.008408482 0.004996074 0.007996625 0.017820178 0.004996074 0.007817658
#> [97] 0.007694340 0.006625684 0.004996074 0.005130044 0.013703933 0.008705654
#> [103] 0.005130044 0.008295057 0.018172661 0.005130044 0.008109875 0.007723696
#> [109] 0.006889129 0.005130044 0.004821500 0.026754476 0.008331153 0.004821500
#> [115] 0.007963081 0.017869091 0.004821500 0.007838034 0.007295755 0.006382087
#> [121] 0.004821500
#>
#> $mean_mase
#> [1] 0.1443847 0.1722253 0.1802104 0.1443847 0.1956282 0.2503591 0.1443847
#> [8] 0.2183439 0.1531998 0.1409593 0.1443847 0.1405491 0.1500054 0.1736017
#> [15] 0.1405491 0.1886507 0.2496264 0.1405491 0.2112424 0.1527229 0.1383295
#> [22] 0.1405491 0.1623733 0.2492993 0.1948363 0.1623558 0.2091101 0.2480531
#> [29] 0.1623733 0.2299184 0.1755608 0.1601103 0.1623558 0.1530152 0.1864536
#> [36] 0.1941715 0.1530152 0.2100379 0.2571236 0.1530152 0.2334909 0.1572210
#> [43] 0.1472043 0.1530152 0.1653849 0.2521815 0.1941727 0.1649185 0.2073869
#> [50] 0.2447382 0.1653849 0.2268945 0.1819947 0.1641347 0.1649185 0.1671285
#> [57] 0.3397478 0.1961630 0.1671285 0.2118363 0.3093108 0.1671285 0.2354963
#> [64] 0.1913844 0.1680301 0.1671285 0.1444253 0.3545446 0.1813529 0.1444253
#> [71] 0.1970089 0.2536064 0.1444253 0.2202398 0.1517424 0.1410410 0.1444253
#> [78] 0.1674420 0.2513480 0.1911680 0.1658348 0.2029873 0.2410994 0.1674420
#> [85] 0.2207274 0.1879665 0.1662600 0.1658348 0.1460992 0.2050398 0.1880013
#> [92] 0.1460992 0.2048237 0.2584120 0.1460992 0.2294458 0.1462064 0.1412333
#> [99] 0.1460992 0.1516616 0.1847884 0.1935217 0.1516616 0.2095773 0.2571389
#> [106] 0.1516616 0.2332759 0.1553623 0.1459342 0.1516616 0.1483513 0.1889385
#> [113] 0.1808231 0.1483513 0.1957116 0.2564030 0.1483513 0.2178565 0.1582895
#> [120] 0.1473050 0.1483513
#>
#> $std_mase
#> [1] 0.01737997 0.06536987 0.02449558 0.01737997 0.02366950 0.03535015
#> [7] 0.01737997 0.02414545 0.02524746 0.01976845 0.01737997 0.01584031
#> [13] 0.02856083 0.02386140 0.01584031 0.02317799 0.03287533 0.01584031
#> [19] 0.02393001 0.02346654 0.01704650 0.01584031 0.01761579 0.17408857
#> [25] 0.02554216 0.01760980 0.02494187 0.03718291 0.01761579 0.02511225
#> [31] 0.02247806 0.01923897 0.01760980 0.01692199 0.06638635 0.02513900
#> [37] 0.01692199 0.02493743 0.03537918 0.01692199 0.02569249 0.02697359
#> [43] 0.02006983 0.01692199 0.01735787 0.17328200 0.02548764 0.01743466
#> [49] 0.02484135 0.03808192 0.01735787 0.02480578 0.02050458 0.01864130
#> [55] 0.01743466 0.01671873 0.25625978 0.02560116 0.01671873 0.02483973
#> [61] 0.03345731 0.01671873 0.02524240 0.02424436 0.01910646 0.01671873
#> [67] 0.01782300 0.63439389 0.02488104 0.01782300 0.02403365 0.03577443
#> [73] 0.01782300 0.02446924 0.02568121 0.01958248 0.01782300 0.01669868
#> [79] 0.17109182 0.02498552 0.01695669 0.02431457 0.03776606 0.01669868
#> [85] 0.02411016 0.01851879 0.01799356 0.01695669 0.01688127 0.13478352
#> [91] 0.02467452 0.01688127 0.02429820 0.03525879 0.01688127 0.02530233
#> [97] 0.02887090 0.01919252 0.01688127 0.01678988 0.06614647 0.02508580
#> [103] 0.01678988 0.02490286 0.03517517 0.01678988 0.02566161 0.02743763
#> [109] 0.01975327 0.01678988 0.01738131 0.12058132 0.02477065 0.01738131
#> [115] 0.02374024 0.03700000 0.01738131 0.02429050 0.02463767 0.01918751
#> [121] 0.01738131
#>
#> $mean_smape
#> [1] 0.01458110 0.01924617 0.01774106 0.01458110 0.01917663 0.02330848
#> [7] 0.01458110 0.02123624 0.01627463 0.01425306 0.01458110 0.01454467
#> [13] 0.01693864 0.01751212 0.01454467 0.01890744 0.02368529 0.01454467
#> [19] 0.02098785 0.01661694 0.01429931 0.01454467 0.01539398 0.02717718
#> [25] 0.01824807 0.01539248 0.01953746 0.02207094 0.01539398 0.02136322
#> [31] 0.01738392 0.01515736 0.01539248 0.01450879 0.01990585 0.01794388
#> [37] 0.01450879 0.01934000 0.02224966 0.01450879 0.02133266 0.01579918
#> [43] 0.01400820 0.01450879 0.01580895 0.02770842 0.01842252 0.01576654
#> [49] 0.01964823 0.02216543 0.01580895 0.02140107 0.01805088 0.01563684
#> [55] 0.01576654 0.01548581 0.04029814 0.01800458 0.01548581 0.01934580
#> [61] 0.02583820 0.01548581 0.02133668 0.01822778 0.01546646 0.01548581
#> [67] 0.01451168 0.05566181 0.01774675 0.01451168 0.01917588 0.02343041
#> [73] 0.01451168 0.02124723 0.01619883 0.01419900 0.01451168 0.01638638
#> [79] 0.02830095 0.01865334 0.01622803 0.01980114 0.02250378 0.01638638
#> [85] 0.02146669 0.01894557 0.01618538 0.01622803 0.01416327 0.02340122
#> [91] 0.01771755 0.01416327 0.01920242 0.02265099 0.01416327 0.02131198
#> [97] 0.01515087 0.01372563 0.01416327 0.01439760 0.01979083 0.01789746
#> [103] 0.01439760 0.01931032 0.02224358 0.01439760 0.02132484 0.01564036
#> [109] 0.01390360 0.01439760 0.01494441 0.02189619 0.01775431 0.01494441
#> [115] 0.01911224 0.02399783 0.01494441 0.02110184 0.01690416 0.01483050
#> [121] 0.01494441
#>
#> $std_smape
#> [1] 0.002287977 0.009336169 0.002759905 0.002287977 0.002687833 0.003144918
#> [7] 0.002287977 0.002682835 0.003481081 0.002346143 0.002287977 0.002169322
#> [13] 0.004788904 0.002784690 0.002169322 0.002748538 0.003003641 0.002169322
#> [19] 0.002750052 0.003246905 0.002141011 0.002169322 0.002192884 0.023145162
#> [25] 0.002681496 0.002192473 0.002645441 0.003046867 0.002192884 0.002656738
#> [31] 0.003433045 0.002164461 0.002192473 0.002125448 0.009062217 0.002635967
#> [37] 0.002125448 0.002615502 0.002892752 0.002125448 0.002650557 0.003529477
#> [43] 0.002195387 0.002125448 0.002186285 0.023398456 0.002697796 0.002195074
#> [49] 0.002661624 0.003144529 0.002186285 0.002662155 0.003324986 0.002132486
#> [55] 0.002195074 0.002026392 0.036243778 0.002668416 0.002026392 0.002642333
#> [61] 0.002709287 0.002026392 0.002651616 0.003573911 0.002041651 0.002026392
#> [67] 0.002383759 0.121689618 0.002834234 0.002383759 0.002765792 0.003320646
#> [73] 0.002383759 0.002753038 0.003575383 0.002368294 0.002383759 0.002163010
#> [79] 0.023852930 0.002707629 0.002194191 0.002673228 0.003198182 0.002163010
#> [85] 0.002666980 0.003224892 0.002118007 0.002194191 0.002177624 0.019273784
#> [91] 0.002657626 0.002177624 0.002621636 0.002943346 0.002177624 0.002655450
#> [97] 0.003674807 0.002215693 0.002177624 0.002108432 0.009028028 0.002623595
#> [103] 0.002108432 0.002605521 0.002883085 0.002108432 0.002640301 0.003564813
#> [109] 0.002157184 0.002108432 0.002360369 0.018456251 0.002847672 0.002360369
#> [115] 0.002780902 0.003350219 0.002360369 0.002782340 0.003533362 0.002353924
#> [121] 0.002360369
#>
#> attr(,"class")
#> [1] "kssa.table"
#> attr(,"row.names")
#> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
#> [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
#> [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
#> [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
#> [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
#> [91] 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108
#> [109] 109 110 111 112 113 114 115 116 117 118 119 120 121
#> attr(,"groups")
#> # A tibble: 11 × 2
#> start_methods .rows
#> <chr> <list<int>>
#> 1 StructTS [11]
#> 2 auto.arima [11]
#> 3 exponential_ma [11]
#> 4 linear_i [11]
#> 5 linear_ma [11]
#> 6 locf [11]
#> 7 seadec [11]
#> 8 simple_ma [11]
#> 9 spline_i [11]
#> 10 stine_i [11]
#> 11 stl [11]
#>
#> [[3]]
#> start_methods actual_methods percent_md rmse cor mase
#> 1 auto.arima auto.arima 0.2008547 14.05045 0.9862110 0.1520912
#> 2 auto.arima StructTS 0.2008547 13.26078 0.9877469 0.1450697
#> 3 auto.arima linear_i 0.2008547 13.26078 0.9877469 0.1450697
#> 4 auto.arima spline_i 0.2008547 17.46070 0.9787401 0.1821534
#> 5 auto.arima stine_i 0.2008547 12.79776 0.9885842 0.1423493
#> 6 auto.arima simple_ma 0.2008547 17.38666 0.9789472 0.2052456
#> 7 auto.arima linear_ma 0.2008547 15.76341 0.9826987 0.1830342
#> 8 auto.arima exponential_ma 0.2008547 14.69970 0.9849501 0.1714422
#> 9 auto.arima seadec 0.2008547 13.26078 0.9877469 0.1450697
#> 10 auto.arima locf 0.2008547 24.44539 0.9597547 0.2660188
#> 11 auto.arima stl 0.2008547 13.26078 0.9877469 0.1450697
#> 12 auto.arima auto.arima 0.2008547 12.23557 0.9895579 0.1211136
#> 13 auto.arima StructTS 0.2008547 12.41317 0.9892599 0.1227158
#> 14 auto.arima linear_i 0.2008547 12.41317 0.9892599 0.1227158
#> 15 auto.arima spline_i 0.2008547 13.01043 0.9883102 0.1278515
#> 16 auto.arima stine_i 0.2008547 12.36948 0.9893327 0.1229199
#> 17 auto.arima simple_ma 0.2008547 16.25045 0.9815702 0.1813506
#> 18 auto.arima linear_ma 0.2008547 15.22911 0.9838173 0.1641865
#> 19 auto.arima exponential_ma 0.2008547 14.56711 0.9851995 0.1528485
#> 20 auto.arima seadec 0.2008547 12.41317 0.9892599 0.1227158
#> 21 auto.arima locf 0.2008547 18.80415 0.9760303 0.2293225
#> 22 auto.arima stl 0.2008547 12.41317 0.9892599 0.1227158
#> 23 auto.arima auto.arima 0.2008547 13.68033 0.9870289 0.1236412
#> 24 auto.arima StructTS 0.2008547 13.62518 0.9871150 0.1228913
#> 25 auto.arima linear_i 0.2008547 13.62518 0.9871150 0.1228913
#> 26 auto.arima spline_i 0.2008547 14.37310 0.9856006 0.1265797
#> 27 auto.arima stine_i 0.2008547 13.43526 0.9874697 0.1212248
#> 28 auto.arima simple_ma 0.2008547 18.07289 0.9773955 0.2131502
#> 29 auto.arima linear_ma 0.2008547 16.36159 0.9815066 0.1827647
#> 30 auto.arima exponential_ma 0.2008547 15.25456 0.9839176 0.1607131
#> 31 auto.arima seadec 0.2008547 13.62518 0.9871150 0.1228913
#> 32 auto.arima locf 0.2008547 22.24499 0.9656584 0.2197065
#> 33 auto.arima stl 0.2008547 13.62518 0.9871150 0.1228913
#> 34 auto.arima auto.arima 0.2008547 13.51630 0.9873425 0.1294691
#> 35 auto.arima StructTS 0.2008547 13.54310 0.9873099 0.1298128
#> 36 auto.arima linear_i 0.2008547 13.54310 0.9873099 0.1298128
#> 37 auto.arima spline_i 0.2008547 14.18836 0.9860269 0.1455676
#> 38 auto.arima stine_i 0.2008547 13.35660 0.9876621 0.1264545
#> 39 auto.arima simple_ma 0.2008547 17.44570 0.9788978 0.1987238
#> 40 auto.arima linear_ma 0.2008547 15.89755 0.9825107 0.1740191
#> 41 auto.arima exponential_ma 0.2008547 14.84470 0.9847676 0.1571786
#> 42 auto.arima seadec 0.2008547 13.54310 0.9873099 0.1298128
#> 43 auto.arima locf 0.2008547 26.28794 0.9521268 0.2493342
#> 44 auto.arima stl 0.2008547 13.54310 0.9873099 0.1298128
#> 45 auto.arima auto.arima 0.2008547 14.49103 0.9853467 0.1456672
#> 46 auto.arima StructTS 0.2008547 14.68414 0.9849427 0.1506975
#> 47 auto.arima linear_i 0.2008547 14.68414 0.9849427 0.1506975
#> 48 auto.arima spline_i 0.2008547 14.43173 0.9854884 0.1418050
#> 49 auto.arima stine_i 0.2008547 14.36652 0.9855905 0.1478797
#> 50 auto.arima simple_ma 0.2008547 17.86777 0.9777121 0.1966454
#> 51 auto.arima linear_ma 0.2008547 16.31030 0.9814238 0.1779458
#> 52 auto.arima exponential_ma 0.2008547 15.20125 0.9838633 0.1661939
#> 53 auto.arima seadec 0.2008547 14.68414 0.9849427 0.1506975
#> 54 auto.arima locf 0.2008547 25.13821 0.9576172 0.2609143
#> 55 auto.arima stl 0.2008547 14.68414 0.9849427 0.1506975
#> 56 auto.arima auto.arima 0.2008547 17.56464 0.9798297 0.2178347
#> 57 auto.arima StructTS 0.2008547 12.52344 0.9890532 0.1307818
#> 58 auto.arima linear_i 0.2008547 12.52344 0.9890532 0.1307818
#> 59 auto.arima spline_i 0.2008547 15.07084 0.9843531 0.1524475
#> 60 auto.arima stine_i 0.2008547 12.14587 0.9897039 0.1272850
#> 61 auto.arima simple_ma 0.2008547 16.07550 0.9819875 0.1908883
#> 62 auto.arima linear_ma 0.2008547 14.66767 0.9849977 0.1695413
#> 63 auto.arima exponential_ma 0.2008547 13.77509 0.9867569 0.1550335
#> 64 auto.arima seadec 0.2008547 12.52344 0.9890532 0.1307818
#> 65 auto.arima locf 0.2008547 15.84165 0.9825336 0.2050358
#> 66 auto.arima stl 0.2008547 12.52344 0.9890532 0.1307818
#> 67 auto.arima auto.arima 0.2008547 18.95263 0.9750836 0.1679311
#> 68 auto.arima StructTS 0.2008547 18.45104 0.9764333 0.1664415
#> 69 auto.arima linear_i 0.2008547 18.45104 0.9764333 0.1664415
#> 70 auto.arima spline_i 0.2008547 21.50884 0.9680978 0.1787719
#> 71 auto.arima stine_i 0.2008547 19.16696 0.9745170 0.1645495
#> 72 auto.arima simple_ma 0.2008547 20.95326 0.9695893 0.2430307
#> 73 auto.arima linear_ma 0.2008547 20.21137 0.9717265 0.2215034
#> 74 auto.arima exponential_ma 0.2008547 19.90514 0.9725763 0.2074047
#> 75 auto.arima seadec 0.2008547 18.45104 0.9764333 0.1664415
#> 76 auto.arima locf 0.2008547 33.23956 0.9241565 0.3071036
#> 77 auto.arima stl 0.2008547 18.45104 0.9764333 0.1664415
#> 78 auto.arima auto.arima 0.2008547 18.51953 0.9760764 0.1605157
#> 79 auto.arima StructTS 0.2008547 18.15947 0.9770245 0.1647450
#> 80 auto.arima linear_i 0.2008547 18.15947 0.9770245 0.1647450
#> 81 auto.arima spline_i 0.2008547 20.63667 0.9703645 0.1604032
#> 82 auto.arima stine_i 0.2008547 19.85804 0.9724798 0.1684251
#> 83 auto.arima simple_ma 0.2008547 25.36308 0.9551598 0.2604343
#> 84 auto.arima linear_ma 0.2008547 24.42791 0.9583861 0.2375384
#> 85 auto.arima exponential_ma 0.2008547 24.05594 0.9596365 0.2253155
#> 86 auto.arima seadec 0.2008547 18.15947 0.9770245 0.1647450
#> 87 auto.arima locf 0.2008547 30.15453 0.9384529 0.2919867
#> 88 auto.arima stl 0.2008547 18.15947 0.9770245 0.1647450
#> 89 auto.arima auto.arima 0.2008547 13.65127 0.9870137 0.1500648
#> 90 auto.arima StructTS 0.2008547 11.88619 0.9901496 0.1363548
#> 91 auto.arima linear_i 0.2008547 11.88619 0.9901496 0.1363548
#> 92 auto.arima spline_i 0.2008547 14.54728 0.9853985 0.1863256
#> 93 auto.arima stine_i 0.2008547 11.50398 0.9907733 0.1281709
#> 94 auto.arima simple_ma 0.2008547 17.06244 0.9796917 0.2097223
#> 95 auto.arima linear_ma 0.2008547 15.39275 0.9834809 0.1862197
#> 96 auto.arima exponential_ma 0.2008547 14.11937 0.9861042 0.1677382
#> 97 auto.arima seadec 0.2008547 11.88619 0.9901496 0.1363548
#> 98 auto.arima locf 0.2008547 22.78777 0.9638603 0.2477704
#> 99 auto.arima stl 0.2008547 11.88619 0.9901496 0.1363548
#> 100 auto.arima auto.arima 0.2008547 13.75520 0.9868599 0.1317252
#> 101 auto.arima StructTS 0.2008547 13.92680 0.9865457 0.1359811
#> 102 auto.arima linear_i 0.2008547 13.92680 0.9865457 0.1359811
#> 103 auto.arima spline_i 0.2008547 14.01799 0.9863590 0.1253231
#> 104 auto.arima stine_i 0.2008547 13.51692 0.9873579 0.1340365
#> 105 auto.arima simple_ma 0.2008547 18.44760 0.9762613 0.2132325
#> 106 auto.arima linear_ma 0.2008547 16.95159 0.9799757 0.1897540
#> 107 auto.arima exponential_ma 0.2008547 15.89943 0.9823970 0.1721490
#> 108 auto.arima seadec 0.2008547 13.92680 0.9865457 0.1359811
#> 109 auto.arima locf 0.2008547 19.20502 0.9742437 0.2190709
#> 110 auto.arima stl 0.2008547 13.92680 0.9865457 0.1359811
#> 111 StructTS auto.arima 0.2008547 29.24626 0.9437335 0.3361452
#> 112 StructTS StructTS 0.2008547 13.16693 0.9878668 0.1474230
#> 113 StructTS linear_i 0.2008547 13.16693 0.9878668 0.1474230
#> 114 StructTS spline_i 0.2008547 17.07738 0.9795443 0.1822989
#> 115 StructTS stine_i 0.2008547 12.66064 0.9887803 0.1434193
#> 116 StructTS simple_ma 0.2008547 17.46070 0.9786610 0.2129044
#> 117 StructTS linear_ma 0.2008547 15.83604 0.9824521 0.1902569
#> 118 StructTS exponential_ma 0.2008547 14.75726 0.9847571 0.1773006
#> 119 StructTS seadec 0.2008547 13.16693 0.9878668 0.1474230
#> 120 StructTS locf 0.2008547 23.93776 0.9611124 0.2638885
#> 121 StructTS stl 0.2008547 13.16693 0.9878668 0.1474230
#> 122 StructTS auto.arima 0.2008547 12.00220 0.9898940 0.1206178
#> 123 StructTS StructTS 0.2008547 12.14597 0.9896554 0.1220706
#> 124 StructTS linear_i 0.2008547 12.14597 0.9896554 0.1220706
#> 125 StructTS spline_i 0.2008547 12.30524 0.9894441 0.1223523
#> 126 StructTS stine_i 0.2008547 11.64403 0.9904814 0.1177114
#> 127 StructTS simple_ma 0.2008547 16.13772 0.9817287 0.1875100
#> 128 StructTS linear_ma 0.2008547 15.10236 0.9840000 0.1689256
#> 129 StructTS exponential_ma 0.2008547 14.40624 0.9854451 0.1564295
#> 130 StructTS seadec 0.2008547 12.14597 0.9896554 0.1220706
#> 131 StructTS locf 0.2008547 17.57150 0.9788851 0.2222808
#> 132 StructTS stl 0.2008547 12.14597 0.9896554 0.1220706
#> 133 StructTS auto.arima 0.2008547 13.94336 0.9864681 0.1282949
#> 134 StructTS StructTS 0.2008547 13.88762 0.9865591 0.1278611
#> 135 StructTS linear_i 0.2008547 13.88762 0.9865591 0.1278611
#> 136 StructTS spline_i 0.2008547 14.35673 0.9855901 0.1269700
#> 137 StructTS stine_i 0.2008547 13.67704 0.9869660 0.1255020
#> 138 StructTS simple_ma 0.2008547 18.12839 0.9771410 0.2205814
#> 139 StructTS linear_ma 0.2008547 16.51746 0.9810563 0.1906412
#> 140 StructTS exponential_ma 0.2008547 15.48559 0.9833430 0.1686777
#> 141 StructTS seadec 0.2008547 13.88762 0.9865591 0.1278611
#> 142 StructTS locf 0.2008547 22.10437 0.9658917 0.2221621
#> 143 StructTS stl 0.2008547 13.88762 0.9865591 0.1278611
#> 144 StructTS auto.arima 0.2008547 13.69045 0.9869586 0.1346936
#> 145 StructTS StructTS 0.2008547 13.71472 0.9869291 0.1354484
#> 146 StructTS linear_i 0.2008547 13.71472 0.9869291 0.1354484
#> 147 StructTS spline_i 0.2008547 13.66190 0.9869925 0.1400020
#> 148 StructTS stine_i 0.2008547 13.47197 0.9873937 0.1291643
#> 149 StructTS simple_ma 0.2008547 17.61452 0.9783818 0.2076810
#> 150 StructTS linear_ma 0.2008547 16.14134 0.9818811 0.1835442
#> 151 StructTS exponential_ma 0.2008547 15.12489 0.9841100 0.1673099
#> 152 StructTS seadec 0.2008547 13.71472 0.9869291 0.1354484
#> 153 StructTS locf 0.2008547 25.86899 0.9533957 0.2460354
#> 154 StructTS stl 0.2008547 13.71472 0.9869291 0.1354484
#> 155 StructTS auto.arima 0.2008547 14.53868 0.9851722 0.1480766
#> 156 StructTS StructTS 0.2008547 14.72881 0.9847686 0.1516692
#> 157 StructTS linear_i 0.2008547 14.72881 0.9847686 0.1516692
#> 158 StructTS spline_i 0.2008547 14.43699 0.9853945 0.1430775
#> 159 StructTS stine_i 0.2008547 14.37028 0.9855046 0.1481566
#> 160 StructTS simple_ma 0.2008547 17.83165 0.9776796 0.2028210
#> 161 StructTS linear_ma 0.2008547 16.30693 0.9813297 0.1825600
#> 162 StructTS exponential_ma 0.2008547 15.21749 0.9837400 0.1694672
#> 163 StructTS seadec 0.2008547 14.72881 0.9847686 0.1516692
#> 164 StructTS locf 0.2008547 24.67727 0.9588297 0.2588678
#> 165 StructTS stl 0.2008547 14.72881 0.9847686 0.1516692
#> 166 StructTS auto.arima 0.2008547 18.33515 0.9777831 0.2271341
#> 167 StructTS StructTS 0.2008547 12.58861 0.9888733 0.1326990
#> 168 StructTS linear_i 0.2008547 12.58861 0.9888733 0.1326990
#> 169 StructTS spline_i 0.2008547 14.77224 0.9848148 0.1520344
#> 170 StructTS stine_i 0.2008547 12.20866 0.9895357 0.1282693
#> 171 StructTS simple_ma 0.2008547 16.18820 0.9816412 0.1981291
#> 172 StructTS linear_ma 0.2008547 14.80248 0.9846440 0.1760081
#> 173 StructTS exponential_ma 0.2008547 13.92196 0.9864048 0.1603862
#> 174 StructTS seadec 0.2008547 12.58861 0.9888733 0.1326990
#> 175 StructTS locf 0.2008547 15.51486 0.9831360 0.2055535
#> 176 StructTS stl 0.2008547 12.58861 0.9888733 0.1326990
#> 177 StructTS auto.arima 0.2008547 18.46299 0.9762370 0.1728559
#> 178 StructTS StructTS 0.2008547 18.53464 0.9760727 0.1728060
#> 179 StructTS linear_i 0.2008547 18.53464 0.9760727 0.1728060
#> 180 StructTS spline_i 0.2008547 21.86942 0.9668423 0.1837592
#> 181 StructTS stine_i 0.2008547 19.20607 0.9742609 0.1703469
#> 182 StructTS simple_ma 0.2008547 20.72467 0.9700918 0.2477011
#> 183 StructTS linear_ma 0.2008547 20.04059 0.9720501 0.2263258
#> 184 StructTS exponential_ma 0.2008547 19.79891 0.9727137 0.2123629
#> 185 StructTS seadec 0.2008547 18.53464 0.9760727 0.1728060
#> 186 StructTS locf 0.2008547 33.32532 0.9233491 0.3167065
#> 187 StructTS stl 0.2008547 18.53464 0.9760727 0.1728060
#> 188 StructTS auto.arima 0.2008547 18.80029 0.9752289 0.1688386
#> 189 StructTS StructTS 0.2008547 18.34183 0.9764655 0.1731697
#> 190 StructTS linear_i 0.2008547 18.34183 0.9764655 0.1731697
#> 191 StructTS spline_i 0.2008547 20.72343 0.9698950 0.1689946
#> 192 StructTS stine_i 0.2008547 20.03207 0.9718588 0.1784507
#> 193 StructTS simple_ma 0.2008547 25.36212 0.9549156 0.2696724
#> 194 StructTS linear_ma 0.2008547 24.48605 0.9579602 0.2469145
#> 195 StructTS exponential_ma 0.2008547 24.14980 0.9590991 0.2347141
#> 196 StructTS seadec 0.2008547 18.34183 0.9764655 0.1731697
#> 197 StructTS locf 0.2008547 30.00934 0.9385313 0.2974266
#> 198 StructTS stl 0.2008547 18.34183 0.9764655 0.1731697
#> 199 StructTS auto.arima 0.2008547 13.77719 0.9866909 0.1538767
#> 200 StructTS StructTS 0.2008547 12.02768 0.9898712 0.1402852
#> 201 StructTS linear_i 0.2008547 12.02768 0.9898712 0.1402852
#> 202 StructTS spline_i 0.2008547 14.17408 0.9859768 0.1860083
#> 203 StructTS stine_i 0.2008547 11.60859 0.9905660 0.1310135
#> 204 StructTS simple_ma 0.2008547 17.15252 0.9793722 0.2172399
#> 205 StructTS linear_ma 0.2008547 15.54869 0.9830619 0.1948198
#> 206 StructTS exponential_ma 0.2008547 14.31843 0.9856419 0.1768063
#> 207 StructTS seadec 0.2008547 12.02768 0.9898712 0.1402852
#> 208 StructTS locf 0.2008547 22.52124 0.9645061 0.2478407
#> 209 StructTS stl 0.2008547 12.02768 0.9898712 0.1402852
#> 210 StructTS auto.arima 0.2008547 13.65518 0.9870119 0.1317194
#> 211 StructTS StructTS 0.2008547 14.00630 0.9863310 0.1404146
#> 212 StructTS linear_i 0.2008547 14.00630 0.9863310 0.1404146
#> 213 StructTS spline_i 0.2008547 13.77703 0.9867757 0.1265011
#> 214 StructTS stine_i 0.2008547 13.58298 0.9871758 0.1375588
#> 215 StructTS simple_ma 0.2008547 18.48375 0.9760369 0.2191988
#> 216 StructTS linear_ma 0.2008547 17.04826 0.9796365 0.1962856
#> 217 StructTS exponential_ma 0.2008547 16.03489 0.9820003 0.1786493
#> 218 StructTS seadec 0.2008547 14.00630 0.9863310 0.1404146
#> 219 StructTS locf 0.2008547 19.12958 0.9743054 0.2228296
#> 220 StructTS stl 0.2008547 14.00630 0.9863310 0.1404146
#> 221 linear_i auto.arima 0.2008547 29.08513 0.9437895 0.3463565
#> 222 linear_i StructTS 0.2008547 12.37066 0.9892373 0.1401110
#> 223 linear_i linear_i 0.2008547 12.37066 0.9892373 0.1401110
#> 224 linear_i spline_i 0.2008547 16.29402 0.9812707 0.1775668
#> 225 linear_i stine_i 0.2008547 11.59951 0.9905525 0.1310617
#> 226 linear_i simple_ma 0.2008547 16.92258 0.9797800 0.2192522
#> 227 linear_i linear_ma 0.2008547 15.24981 0.9835925 0.1942247
#> 228 linear_i exponential_ma 0.2008547 14.12512 0.9859218 0.1803199
#> 229 linear_i seadec 0.2008547 12.37066 0.9892373 0.1401110
#> 230 linear_i locf 0.2008547 23.29809 0.9626169 0.2672006
#> 231 linear_i stl 0.2008547 12.37066 0.9892373 0.1401110
#> 232 linear_i auto.arima 0.2008547 12.00105 0.9897935 0.1316275
#> 233 linear_i StructTS 0.2008547 12.11009 0.9896119 0.1333617
#> 234 linear_i linear_i 0.2008547 12.11009 0.9896119 0.1333617
#> 235 linear_i spline_i 0.2008547 11.86719 0.9900525 0.1219776
#> 236 linear_i stine_i 0.2008547 11.26300 0.9910059 0.1219469
#> 237 linear_i simple_ma 0.2008547 16.09545 0.9816488 0.2005558
#> 238 linear_i linear_ma 0.2008547 15.11841 0.9838119 0.1820808
#> 239 linear_i exponential_ma 0.2008547 14.44753 0.9852202 0.1702903
#> 240 linear_i seadec 0.2008547 12.11009 0.9896119 0.1333617
#> 241 linear_i locf 0.2008547 16.20696 0.9817499 0.2231097
#> 242 linear_i stl 0.2008547 12.11009 0.9896119 0.1333617
#> 243 linear_i auto.arima 0.2008547 13.95270 0.9862815 0.1407673
#> 244 linear_i StructTS 0.2008547 14.24413 0.9857265 0.1413192
#> 245 linear_i linear_i 0.2008547 14.24413 0.9857265 0.1413192
#> 246 linear_i spline_i 0.2008547 14.38890 0.9853916 0.1382476
#> 247 linear_i stine_i 0.2008547 14.08382 0.9860508 0.1393502
#> 248 linear_i simple_ma 0.2008547 18.27239 0.9765602 0.2381298
#> 249 linear_i linear_ma 0.2008547 16.75331 0.9803269 0.2087794
#> 250 linear_i exponential_ma 0.2008547 15.77818 0.9825435 0.1871574
#> 251 linear_i seadec 0.2008547 14.24413 0.9857265 0.1413192
#> 252 linear_i locf 0.2008547 21.96467 0.9659657 0.2390845
#> 253 linear_i stl 0.2008547 14.24413 0.9857265 0.1413192
#> 254 linear_i auto.arima 0.2008547 13.19519 0.9877774 0.1341996
#> 255 linear_i StructTS 0.2008547 13.76803 0.9867127 0.1447260
#> 256 linear_i linear_i 0.2008547 13.76803 0.9867127 0.1447260
#> 257 linear_i spline_i 0.2008547 13.14571 0.9878729 0.1336200
#> 258 linear_i stine_i 0.2008547 13.50649 0.9872245 0.1375561
#> 259 linear_i simple_ma 0.2008547 17.68558 0.9779994 0.2218729
#> 260 linear_i linear_ma 0.2008547 16.27175 0.9814116 0.1984050
#> 261 linear_i exponential_ma 0.2008547 15.27915 0.9836304 0.1827757
#> 262 linear_i seadec 0.2008547 13.76803 0.9867127 0.1447260
#> 263 linear_i locf 0.2008547 25.67978 0.9536666 0.2539107
#> 264 linear_i stl 0.2008547 13.76803 0.9867127 0.1447260
#> 265 linear_i auto.arima 0.2008547 16.39494 0.9812096 0.1888321
#> 266 linear_i StructTS 0.2008547 14.65797 0.9847744 0.1598819
#> 267 linear_i linear_i 0.2008547 14.65797 0.9847744 0.1598819
#> 268 linear_i spline_i 0.2008547 14.18388 0.9857626 0.1495348
#> 269 linear_i stine_i 0.2008547 14.30428 0.9855034 0.1537220
#> 270 linear_i simple_ma 0.2008547 17.85208 0.9774167 0.2184878
#> 271 linear_i linear_ma 0.2008547 16.33920 0.9810801 0.1966181
#> 272 linear_i exponential_ma 0.2008547 15.23039 0.9835602 0.1822168
#> 273 linear_i seadec 0.2008547 14.65797 0.9847744 0.1598819
#> 274 linear_i locf 0.2008547 24.21561 0.9598746 0.2690949
#> 275 linear_i stl 0.2008547 14.65797 0.9847744 0.1598819
#> 276 linear_i auto.arima 0.2008547 18.10558 0.9781095 0.2466357
#> 277 linear_i StructTS 0.2008547 12.66407 0.9886300 0.1436684
#> 278 linear_i linear_i 0.2008547 12.66407 0.9886300 0.1436684
#> 279 linear_i spline_i 0.2008547 14.37508 0.9854498 0.1524467
#> 280 linear_i stine_i 0.2008547 12.29549 0.9892832 0.1385190
#> 281 linear_i simple_ma 0.2008547 16.16741 0.9815229 0.2128012
#> 282 linear_i linear_ma 0.2008547 14.81292 0.9844831 0.1900824
#> 283 linear_i exponential_ma 0.2008547 13.95465 0.9862157 0.1737358
#> 284 linear_i seadec 0.2008547 12.66407 0.9886300 0.1436684
#> 285 linear_i locf 0.2008547 14.85140 0.9843984 0.2087309
#> 286 linear_i stl 0.2008547 12.66407 0.9886300 0.1436684
#> 287 linear_i auto.arima 0.2008547 20.81067 0.9697043 0.1903842
#> 288 linear_i StructTS 0.2008547 18.51229 0.9759511 0.1815470
#> 289 linear_i linear_i 0.2008547 18.51229 0.9759511 0.1815470
#> 290 linear_i spline_i 0.2008547 21.60487 0.9674675 0.1940609
#> 291 linear_i stine_i 0.2008547 19.25370 0.9739500 0.1780240
#> 292 linear_i simple_ma 0.2008547 21.01255 0.9689800 0.2655649
#> 293 linear_i linear_ma 0.2008547 20.27896 0.9711289 0.2422062
#> 294 linear_i exponential_ma 0.2008547 19.97091 0.9719991 0.2267856
#> 295 linear_i seadec 0.2008547 18.51229 0.9759511 0.1815470
#> 296 linear_i locf 0.2008547 32.78165 0.9253705 0.3197339
#> 297 linear_i stl 0.2008547 18.51229 0.9759511 0.1815470
#> 298 linear_i auto.arima 0.2008547 18.88258 0.9747579 0.1775166
#> 299 linear_i StructTS 0.2008547 18.38269 0.9761296 0.1821436
#> 300 linear_i linear_i 0.2008547 18.38269 0.9761296 0.1821436
#> 301 linear_i spline_i 0.2008547 20.67593 0.9697440 0.1793667
#> 302 linear_i stine_i 0.2008547 20.08558 0.9714326 0.1855446
#> 303 linear_i simple_ma 0.2008547 25.31938 0.9546227 0.2864216
#> 304 linear_i linear_ma 0.2008547 24.49702 0.9575062 0.2629710
#> 305 linear_i exponential_ma 0.2008547 24.18275 0.9585822 0.2499890
#> 306 linear_i seadec 0.2008547 18.38269 0.9761296 0.1821436
#> 307 linear_i locf 0.2008547 29.44202 0.9401523 0.3053999
#> 308 linear_i stl 0.2008547 18.38269 0.9761296 0.1821436
#> 309 linear_i auto.arima 0.2008547 13.99932 0.9861277 0.1692156
#> 310 linear_i StructTS 0.2008547 12.28040 0.9893476 0.1547285
#> 311 linear_i linear_i 0.2008547 12.28040 0.9893476 0.1547285
#> 312 linear_i spline_i 0.2008547 14.12509 0.9859066 0.1942044
#> 313 linear_i stine_i 0.2008547 11.82123 0.9901414 0.1439995
#> 314 linear_i simple_ma 0.2008547 17.35038 0.9787002 0.2349854
#> 315 linear_i linear_ma 0.2008547 15.83380 0.9822731 0.2132515
#> 316 linear_i exponential_ma 0.2008547 14.64640 0.9848375 0.1960503
#> 317 linear_i seadec 0.2008547 12.28040 0.9893476 0.1547285
#> 318 linear_i locf 0.2008547 22.25478 0.9649917 0.2584003
#> 319 linear_i stl 0.2008547 12.28040 0.9893476 0.1547285
#> 320 linear_i auto.arima 0.2008547 13.57663 0.9870158 0.1390008
#> 321 linear_i StructTS 0.2008547 13.96350 0.9862705 0.1486652
#> 322 linear_i linear_i 0.2008547 13.96350 0.9862705 0.1486652
#> 323 linear_i spline_i 0.2008547 13.48089 0.9871992 0.1311850
#> 324 linear_i stine_i 0.2008547 13.51668 0.9871651 0.1423191
#> 325 linear_i simple_ma 0.2008547 18.40914 0.9760008 0.2368374
#> 326 linear_i linear_ma 0.2008547 16.98776 0.9795837 0.2117597
#> 327 linear_i exponential_ma 0.2008547 15.96427 0.9819832 0.1923946
#> 328 linear_i seadec 0.2008547 13.96350 0.9862705 0.1486652
#> 329 linear_i locf 0.2008547 18.70046 0.9752063 0.2265701
#> 330 linear_i stl 0.2008547 13.96350 0.9862705 0.1486652
#> 331 spline_i auto.arima 0.2008547 28.51853 0.9468286 0.3329317
#> 332 spline_i StructTS 0.2008547 12.28840 0.9895432 0.1384766
#> 333 spline_i linear_i 0.2008547 12.28840 0.9895432 0.1384766
#> 334 spline_i spline_i 0.2008547 16.08358 0.9820484 0.1677372
#> 335 spline_i stine_i 0.2008547 11.59777 0.9906992 0.1322711
#> 336 spline_i simple_ma 0.2008547 17.25617 0.9793179 0.2198431
#> 337 spline_i linear_ma 0.2008547 15.48029 0.9833646 0.1940624
#> 338 spline_i exponential_ma 0.2008547 14.28520 0.9858312 0.1788255
#> 339 spline_i seadec 0.2008547 12.28840 0.9895432 0.1384766
#> 340 spline_i locf 0.2008547 24.16463 0.9607532 0.2773776
#> 341 spline_i stl 0.2008547 12.28840 0.9895432 0.1384766
#> 342 spline_i auto.arima 0.2008547 11.99174 0.9899854 0.1264787
#> 343 spline_i StructTS 0.2008547 12.13013 0.9897606 0.1285627
#> 344 spline_i linear_i 0.2008547 12.13013 0.9897606 0.1285627
#> 345 spline_i spline_i 0.2008547 11.57625 0.9906989 0.1104864
#> 346 spline_i stine_i 0.2008547 11.60256 0.9906190 0.1222527
#> 347 spline_i simple_ma 0.2008547 16.23928 0.9816340 0.1964328
#> 348 spline_i linear_ma 0.2008547 15.21591 0.9838804 0.1773255
#> 349 spline_i exponential_ma 0.2008547 14.52536 0.9853164 0.1652914
#> 350 spline_i seadec 0.2008547 12.13013 0.9897606 0.1285627
#> 351 spline_i locf 0.2008547 17.63917 0.9788914 0.2329877
#> 352 spline_i stl 0.2008547 12.13013 0.9897606 0.1285627
#> 353 spline_i auto.arima 0.2008547 13.48530 0.9873541 0.1285990
#> 354 spline_i StructTS 0.2008547 13.69578 0.9869968 0.1314953
#> 355 spline_i linear_i 0.2008547 13.69578 0.9869968 0.1314953
#> 356 spline_i spline_i 0.2008547 14.06464 0.9862351 0.1249484
#> 357 spline_i stine_i 0.2008547 13.54342 0.9872855 0.1317870
#> 358 spline_i simple_ma 0.2008547 18.01853 0.9775730 0.2320899
#> 359 spline_i linear_ma 0.2008547 16.37352 0.9815076 0.2014457
#> 360 spline_i exponential_ma 0.2008547 15.32489 0.9837887 0.1788103
#> 361 spline_i seadec 0.2008547 13.69578 0.9869968 0.1314953
#> 362 spline_i locf 0.2008547 21.99131 0.9664803 0.2320996
#> 363 spline_i stl 0.2008547 13.69578 0.9869968 0.1314953
#> 364 spline_i auto.arima 0.2008547 13.26191 0.9878726 0.1353955
#> 365 spline_i StructTS 0.2008547 13.29195 0.9878349 0.1363937
#> 366 spline_i linear_i 0.2008547 13.29195 0.9878349 0.1363937
#> 367 spline_i spline_i 0.2008547 12.81448 0.9887054 0.1217934
#> 368 spline_i stine_i 0.2008547 13.03406 0.9883122 0.1302473
#> 369 spline_i simple_ma 0.2008547 17.42289 0.9790145 0.2150772
#> 370 spline_i linear_ma 0.2008547 15.89174 0.9825787 0.1906222
#> 371 spline_i exponential_ma 0.2008547 14.83311 0.9848434 0.1744611
#> 372 spline_i seadec 0.2008547 13.29195 0.9878349 0.1363937
#> 373 spline_i locf 0.2008547 25.87557 0.9538080 0.2538466
#> 374 spline_i stl 0.2008547 13.29195 0.9878349 0.1363937
#> 375 spline_i auto.arima 0.2008547 14.45483 0.9854373 0.1553745
#> 376 spline_i StructTS 0.2008547 14.46755 0.9854094 0.1557970
#> 377 spline_i linear_i 0.2008547 14.46755 0.9854094 0.1557970
#> 378 spline_i spline_i 0.2008547 13.87151 0.9866019 0.1334132
#> 379 spline_i stine_i 0.2008547 14.09744 0.9861480 0.1499345
#> 380 spline_i simple_ma 0.2008547 17.77051 0.9779923 0.2139080
#> 381 spline_i linear_ma 0.2008547 16.20969 0.9816850 0.1922015
#> 382 spline_i exponential_ma 0.2008547 15.08326 0.9841411 0.1771740
#> 383 spline_i seadec 0.2008547 14.46755 0.9854094 0.1557970
#> 384 spline_i locf 0.2008547 24.89960 0.9585523 0.2740202
#> 385 spline_i stl 0.2008547 14.46755 0.9854094 0.1557970
#> 386 spline_i auto.arima 0.2008547 41.08792 0.8998448 0.5469436
#> 387 spline_i StructTS 0.2008547 12.16554 0.9896910 0.1355149
#> 388 spline_i linear_i 0.2008547 12.16554 0.9896910 0.1355149
#> 389 spline_i spline_i 0.2008547 14.20000 0.9861281 0.1469668
#> 390 spline_i stine_i 0.2008547 11.62973 0.9905770 0.1274333
#> 391 spline_i simple_ma 0.2008547 16.01389 0.9821538 0.2096878
#> 392 spline_i linear_ma 0.2008547 14.52658 0.9853096 0.1853784
#> 393 spline_i exponential_ma 0.2008547 13.57577 0.9871598 0.1671987
#> 394 spline_i seadec 0.2008547 12.16554 0.9896910 0.1355149
#> 395 spline_i locf 0.2008547 15.25294 0.9838515 0.2102033
#> 396 spline_i stl 0.2008547 12.16554 0.9896910 0.1355149
#> 397 spline_i auto.arima 0.2008547 18.26829 0.9769554 0.1761545
#> 398 spline_i StructTS 0.2008547 18.33975 0.9767962 0.1761660
#> 399 spline_i linear_i 0.2008547 18.33975 0.9767962 0.1761660
#> 400 spline_i spline_i 0.2008547 21.70787 0.9676878 0.1836986
#> 401 spline_i stine_i 0.2008547 19.02539 0.9749862 0.1734478
#> 402 spline_i simple_ma 0.2008547 20.83369 0.9700274 0.2607818
#> 403 spline_i linear_ma 0.2008547 20.07270 0.9721984 0.2369788
#> 404 spline_i exponential_ma 0.2008547 19.76000 0.9730573 0.2214621
#> 405 spline_i seadec 0.2008547 18.33975 0.9767962 0.1761660
#> 406 spline_i locf 0.2008547 33.04072 0.9253946 0.3205641
#> 407 spline_i stl 0.2008547 18.33975 0.9767962 0.1761660
#> 408 spline_i auto.arima 0.2008547 18.70728 0.9756193 0.1659811
#> 409 spline_i StructTS 0.2008547 18.00220 0.9774691 0.1735574
#> 410 spline_i linear_i 0.2008547 18.00220 0.9774691 0.1735574
#> 411 spline_i spline_i 0.2008547 20.33518 0.9712303 0.1628913
#> 412 spline_i stine_i 0.2008547 19.68110 0.9730144 0.1763152
#> 413 spline_i simple_ma 0.2008547 25.19792 0.9557971 0.2815975
#> 414 spline_i linear_ma 0.2008547 24.28727 0.9589192 0.2561988
#> 415 spline_i exponential_ma 0.2008547 23.92736 0.9601224 0.2421383
#> 416 spline_i seadec 0.2008547 18.00220 0.9774691 0.1735574
#> 417 spline_i locf 0.2008547 29.79284 0.9399231 0.3024552
#> 418 spline_i stl 0.2008547 18.00220 0.9774691 0.1735574
#> 419 spline_i auto.arima 0.2008547 13.42867 0.9874441 0.1557549
#> 420 spline_i StructTS 0.2008547 11.62762 0.9906082 0.1415275
#> 421 spline_i linear_i 0.2008547 11.62762 0.9906082 0.1415275
#> 422 spline_i spline_i 0.2008547 14.19133 0.9860709 0.1918689
#> 423 spline_i stine_i 0.2008547 11.08008 0.9914823 0.1301703
#> 424 spline_i simple_ma 0.2008547 17.28961 0.9791886 0.2298836
#> 425 spline_i linear_ma 0.2008547 15.59256 0.9830874 0.2049863
#> 426 spline_i exponential_ma 0.2008547 14.26976 0.9858426 0.1850442
#> 427 spline_i seadec 0.2008547 11.62762 0.9906082 0.1415275
#> 428 spline_i locf 0.2008547 22.35475 0.9652818 0.2551429
#> 429 spline_i stl 0.2008547 11.62762 0.9906082 0.1415275
#> 430 spline_i auto.arima 0.2008547 13.11632 0.9880682 0.1267849
#> 431 spline_i StructTS 0.2008547 13.68571 0.9870102 0.1435005
#> 432 spline_i linear_i 0.2008547 13.68571 0.9870102 0.1435005
#> 433 spline_i spline_i 0.2008547 13.11617 0.9880652 0.1182599
#> 434 spline_i stine_i 0.2008547 13.18731 0.9879603 0.1384735
#> 435 spline_i simple_ma 0.2008547 18.49871 0.9761545 0.2351566
#> 436 spline_i linear_ma 0.2008547 16.95815 0.9799757 0.2090375
#> 437 spline_i exponential_ma 0.2008547 15.85586 0.9825047 0.1896072
#> 438 spline_i seadec 0.2008547 13.68571 0.9870102 0.1435005
#> 439 spline_i locf 0.2008547 18.91262 0.9750716 0.2254226
#> 440 spline_i stl 0.2008547 13.68571 0.9870102 0.1435005
#> 441 stine_i auto.arima 0.2008547 28.93505 0.9443146 0.3435826
#> 442 stine_i StructTS 0.2008547 12.35089 0.9892734 0.1397168
#> 443 stine_i linear_i 0.2008547 12.35089 0.9892734 0.1397168
#> 444 stine_i spline_i 0.2008547 16.24676 0.9813755 0.1754545
#> 445 stine_i stine_i 0.2008547 11.66191 0.9904534 0.1325025
#> 446 stine_i simple_ma 0.2008547 16.92636 0.9797695 0.2195368
#> 447 stine_i linear_ma 0.2008547 15.24675 0.9835986 0.1943986
#> 448 stine_i exponential_ma 0.2008547 14.11756 0.9859367 0.1803987
#> 449 stine_i seadec 0.2008547 12.35089 0.9892734 0.1397168
#> 450 stine_i locf 0.2008547 23.36233 0.9624182 0.2683961
#> 451 stine_i stl 0.2008547 12.35089 0.9892734 0.1397168
#> 452 stine_i auto.arima 0.2008547 11.99237 0.9898066 0.1310344
#> 453 stine_i StructTS 0.2008547 12.10355 0.9896217 0.1326830
#> 454 stine_i linear_i 0.2008547 12.10355 0.9896217 0.1326830
#> 455 stine_i spline_i 0.2008547 11.82356 0.9901230 0.1205025
#> 456 stine_i stine_i 0.2008547 11.23373 0.9910511 0.1208602
#> 457 stine_i simple_ma 0.2008547 16.10748 0.9816183 0.2004016
#> 458 stine_i linear_ma 0.2008547 15.12612 0.9837927 0.1818858
#> 459 stine_i exponential_ma 0.2008547 14.45301 0.9852066 0.1700281
#> 460 stine_i seadec 0.2008547 12.10355 0.9896217 0.1326830
#> 461 stine_i locf 0.2008547 16.27047 0.9816073 0.2236587
#> 462 stine_i stl 0.2008547 12.10355 0.9896217 0.1326830
#> 463 stine_i auto.arima 0.2008547 13.88828 0.9864021 0.1391815
#> 464 stine_i StructTS 0.2008547 14.19221 0.9858262 0.1399976
#> 465 stine_i linear_i 0.2008547 14.19221 0.9858262 0.1399976
#> 466 stine_i spline_i 0.2008547 14.32399 0.9855144 0.1355097
#> 467 stine_i stine_i 0.2008547 14.03373 0.9861452 0.1383548
#> 468 stine_i simple_ma 0.2008547 18.26239 0.9765825 0.2379128
#> 469 stine_i linear_ma 0.2008547 16.72958 0.9803799 0.2081973
#> 470 stine_i exponential_ma 0.2008547 15.74569 0.9826126 0.1863672
#> 471 stine_i seadec 0.2008547 14.19221 0.9858262 0.1399976
#> 472 stine_i locf 0.2008547 21.95118 0.9660009 0.2384323
#> 473 stine_i stl 0.2008547 14.19221 0.9858262 0.1399976
#> 474 stine_i auto.arima 0.2008547 13.14997 0.9878604 0.1331680
#> 475 stine_i StructTS 0.2008547 13.73118 0.9867838 0.1437879
#> 476 stine_i linear_i 0.2008547 13.73118 0.9867838 0.1437879
#> 477 stine_i spline_i 0.2008547 13.12777 0.9879072 0.1327059
#> 478 stine_i stine_i 0.2008547 13.47390 0.9872864 0.1368068
#> 479 stine_i simple_ma 0.2008547 17.65265 0.9780818 0.2212611
#> 480 stine_i linear_ma 0.2008547 16.23337 0.9815002 0.1976184
#> 481 stine_i exponential_ma 0.2008547 15.23858 0.9837182 0.1819212
#> 482 stine_i seadec 0.2008547 13.73118 0.9867838 0.1437879
#> 483 stine_i locf 0.2008547 25.69641 0.9535933 0.2545490
#> 484 stine_i stl 0.2008547 13.73118 0.9867838 0.1437879
#> 485 stine_i auto.arima 0.2008547 16.26649 0.9814866 0.1863572
#> 486 stine_i StructTS 0.2008547 14.61687 0.9848565 0.1581758
#> 487 stine_i linear_i 0.2008547 14.61687 0.9848565 0.1581758
#> 488 stine_i spline_i 0.2008547 14.11976 0.9858883 0.1469137
#> 489 stine_i stine_i 0.2008547 14.25983 0.9855904 0.1520179
#> 490 stine_i simple_ma 0.2008547 17.82992 0.9774685 0.2179899
#> 491 stine_i linear_ma 0.2008547 16.31148 0.9811407 0.1959257
#> 492 stine_i exponential_ma 0.2008547 15.19909 0.9836246 0.1814169
#> 493 stine_i seadec 0.2008547 14.61687 0.9848565 0.1581758
#> 494 stine_i locf 0.2008547 24.22087 0.9598631 0.2686599
#> 495 stine_i stl 0.2008547 14.61687 0.9848565 0.1581758
#> 496 stine_i auto.arima 0.2008547 18.05084 0.9782568 0.2460812
#> 497 stine_i StructTS 0.2008547 12.61582 0.9887146 0.1420679
#> 498 stine_i linear_i 0.2008547 12.61582 0.9887146 0.1420679
#> 499 stine_i spline_i 0.2008547 14.32160 0.9855566 0.1507491
#> 500 stine_i stine_i 0.2008547 12.24349 0.9893718 0.1368383
#> 501 stine_i simple_ma 0.2008547 16.15897 0.9815395 0.2130890
#> 502 stine_i linear_ma 0.2008547 14.79191 0.9845250 0.1901124
#> 503 stine_i exponential_ma 0.2008547 13.92491 0.9862724 0.1734887
#> 504 stine_i seadec 0.2008547 12.61582 0.9887146 0.1420679
#> 505 stine_i locf 0.2008547 14.85543 0.9843886 0.2087959
#> 506 stine_i stl 0.2008547 12.61582 0.9887146 0.1420679
#> 507 stine_i auto.arima 0.2008547 20.95441 0.9693003 0.1892632
#> 508 stine_i StructTS 0.2008547 18.48278 0.9760274 0.1800081
#> 509 stine_i linear_i 0.2008547 18.48278 0.9760274 0.1800081
#> 510 stine_i spline_i 0.2008547 21.56884 0.9675720 0.1922471
#> 511 stine_i stine_i 0.2008547 19.21400 0.9740540 0.1759909
#> 512 stine_i simple_ma 0.2008547 21.00746 0.9689939 0.2652395
#> 513 stine_i linear_ma 0.2008547 20.26735 0.9711615 0.2417742
#> 514 stine_i exponential_ma 0.2008547 19.95463 0.9720443 0.2260501
#> 515 stine_i seadec 0.2008547 18.48278 0.9760274 0.1800081
#> 516 stine_i locf 0.2008547 32.77437 0.9253933 0.3194172
#> 517 stine_i stl 0.2008547 18.48278 0.9760274 0.1800081
#> 518 stine_i auto.arima 0.2008547 18.87561 0.9747720 0.1763102
#> 519 stine_i StructTS 0.2008547 18.35605 0.9761953 0.1812515
#> 520 stine_i linear_i 0.2008547 18.35605 0.9761953 0.1812515
#> 521 stine_i spline_i 0.2008547 20.64119 0.9698417 0.1782267
#> 522 stine_i stine_i 0.2008547 20.05778 0.9715072 0.1844694
#> 523 stine_i simple_ma 0.2008547 25.31044 0.9546477 0.2863425
#> 524 stine_i linear_ma 0.2008547 24.48355 0.9575461 0.2627692
#> 525 stine_i exponential_ma 0.2008547 24.16699 0.9586292 0.2495889
#> 526 stine_i seadec 0.2008547 18.35605 0.9761953 0.1812515
#> 527 stine_i locf 0.2008547 29.43510 0.9401772 0.3047960
#> 528 stine_i stl 0.2008547 18.35605 0.9761953 0.1812515
#> 529 stine_i auto.arima 0.2008547 13.89767 0.9863249 0.1665318
#> 530 stine_i StructTS 0.2008547 12.16459 0.9895477 0.1520102
#> 531 stine_i linear_i 0.2008547 12.16459 0.9895477 0.1520102
#> 532 stine_i spline_i 0.2008547 14.10186 0.9859543 0.1939515
#> 533 stine_i stine_i 0.2008547 11.68663 0.9903647 0.1407328
#> 534 stine_i simple_ma 0.2008547 17.30906 0.9787995 0.2343565
#> 535 stine_i linear_ma 0.2008547 15.77070 0.9824131 0.2118775
#> 536 stine_i exponential_ma 0.2008547 14.56668 0.9850017 0.1943367
#> 537 stine_i seadec 0.2008547 12.16459 0.9895477 0.1520102
#> 538 stine_i locf 0.2008547 22.24226 0.9650270 0.2577346
#> 539 stine_i stl 0.2008547 12.16459 0.9895477 0.1520102
#> 540 stine_i auto.arima 0.2008547 13.50229 0.9871570 0.1363738
#> 541 stine_i StructTS 0.2008547 13.91297 0.9863688 0.1469173
#> 542 stine_i linear_i 0.2008547 13.91297 0.9863688 0.1469173
#> 543 stine_i spline_i 0.2008547 13.38598 0.9873800 0.1273619
#> 544 stine_i stine_i 0.2008547 13.46998 0.9872540 0.1407688
#> 545 stine_i simple_ma 0.2008547 18.40242 0.9760145 0.2366296
#> 546 stine_i linear_ma 0.2008547 16.96894 0.9796260 0.2112141
#> 547 stine_i exponential_ma 0.2008547 15.93598 0.9820446 0.1916199
#> 548 stine_i seadec 0.2008547 13.91297 0.9863688 0.1469173
#> 549 stine_i locf 0.2008547 18.70924 0.9751789 0.2269491
#> 550 stine_i stl 0.2008547 13.91297 0.9863688 0.1469173
#> 551 simple_ma auto.arima 0.2008547 31.52480 0.9328165 0.3632785
#> 552 simple_ma StructTS 0.2008547 13.51332 0.9867906 0.1533173
#> 553 simple_ma linear_i 0.2008547 13.25797 0.9872867 0.1511252
#> 554 simple_ma spline_i 0.2008547 17.88249 0.9768140 0.1948276
#> 555 simple_ma stine_i 0.2008547 12.90642 0.9879579 0.1495298
#> 556 simple_ma simple_ma 0.2008547 16.61227 0.9799655 0.2003204
#> 557 simple_ma linear_ma 0.2008547 15.18990 0.9832662 0.1804844
#> 558 simple_ma exponential_ma 0.2008547 14.27301 0.9852232 0.1689167
#> 559 simple_ma seadec 0.2008547 13.51332 0.9867906 0.1533173
#> 560 simple_ma locf 0.2008547 22.50715 0.9637366 0.2331734
#> 561 simple_ma stl 0.2008547 13.25797 0.9872867 0.1511252
#> 562 simple_ma auto.arima 0.2008547 12.59069 0.9884491 0.1367838
#> 563 simple_ma StructTS 0.2008547 12.70567 0.9882287 0.1414592
#> 564 simple_ma linear_i 0.2008547 12.63487 0.9883607 0.1379719
#> 565 simple_ma spline_i 0.2008547 14.93507 0.9838288 0.1643889
#> 566 simple_ma stine_i 0.2008547 12.60903 0.9884105 0.1398831
#> 567 simple_ma simple_ma 0.2008547 15.79734 0.9818046 0.1882333
#> 568 simple_ma linear_ma 0.2008547 14.93988 0.9837257 0.1724348
#> 569 simple_ma exponential_ma 0.2008547 14.36031 0.9849631 0.1622621
#> 570 simple_ma seadec 0.2008547 12.70567 0.9882287 0.1414592
#> 571 simple_ma locf 0.2008547 13.66109 0.9864725 0.1826498
#> 572 simple_ma stl 0.2008547 12.63487 0.9883607 0.1379719
#> 573 simple_ma auto.arima 0.2008547 16.50354 0.9804073 0.1608176
#> 574 simple_ma StructTS 0.2008547 16.41800 0.9805835 0.1601934
#> 575 simple_ma linear_i 0.2008547 16.40801 0.9806062 0.1597256
#> 576 simple_ma spline_i 0.2008547 17.84299 0.9770549 0.1854161
#> 577 simple_ma stine_i 0.2008547 16.51072 0.9803863 0.1643449
#> 578 simple_ma simple_ma 0.2008547 18.89937 0.9742592 0.2299256
#> 579 simple_ma linear_ma 0.2008547 17.81340 0.9771692 0.2069619
#> 580 simple_ma exponential_ma 0.2008547 17.17720 0.9787699 0.1906429
#> 581 simple_ma seadec 0.2008547 16.41800 0.9805835 0.1601934
#> 582 simple_ma locf 0.2008547 22.84355 0.9621127 0.2390128
#> 583 simple_ma stl 0.2008547 16.40801 0.9806062 0.1597256
#> 584 simple_ma auto.arima 0.2008547 15.90395 0.9816713 0.1626175
#> 585 simple_ma StructTS 0.2008547 15.96481 0.9815477 0.1647492
#> 586 simple_ma linear_i 0.2008547 15.90122 0.9816928 0.1633699
#> 587 simple_ma spline_i 0.2008547 16.12873 0.9810933 0.1699519
#> 588 simple_ma stine_i 0.2008547 15.78300 0.9819791 0.1615063
#> 589 simple_ma simple_ma 0.2008547 18.50679 0.9751809 0.2159109
#> 590 simple_ma linear_ma 0.2008547 17.51507 0.9777924 0.1986419
#> 591 simple_ma exponential_ma 0.2008547 16.84672 0.9794658 0.1882434
#> 592 simple_ma seadec 0.2008547 15.96481 0.9815477 0.1647492
#> 593 simple_ma locf 0.2008547 26.09428 0.9507002 0.2480919
#> 594 simple_ma stl 0.2008547 15.90122 0.9816928 0.1633699
#> 595 simple_ma auto.arima 0.2008547 15.89220 0.9816508 0.1753439
#> 596 simple_ma StructTS 0.2008547 15.88405 0.9816540 0.1752688
#> 597 simple_ma linear_i 0.2008547 15.88405 0.9816540 0.1752688
#> 598 simple_ma spline_i 0.2008547 16.86139 0.9793441 0.1910671
#> 599 simple_ma stine_i 0.2008547 15.69516 0.9821005 0.1729210
#> 600 simple_ma simple_ma 0.2008547 18.14623 0.9760281 0.2102404
#> 601 simple_ma linear_ma 0.2008547 16.86687 0.9792960 0.1929564
#> 602 simple_ma exponential_ma 0.2008547 15.93998 0.9815146 0.1803550
#> 603 simple_ma seadec 0.2008547 15.88405 0.9816540 0.1752688
#> 604 simple_ma locf 0.2008547 23.55267 0.9605947 0.2405383
#> 605 simple_ma stl 0.2008547 15.88405 0.9816540 0.1752688
#> 606 simple_ma auto.arima 0.2008547 21.51945 0.9680263 0.2750518
#> 607 simple_ma StructTS 0.2008547 14.76976 0.9841208 0.1587129
#> 608 simple_ma linear_i 0.2008547 14.77889 0.9841000 0.1581444
#> 609 simple_ma spline_i 0.2008547 16.79690 0.9794577 0.1789912
#> 610 simple_ma stine_i 0.2008547 14.61119 0.9844688 0.1573056
#> 611 simple_ma simple_ma 0.2008547 16.73172 0.9797188 0.1991931
#> 612 simple_ma linear_ma 0.2008547 15.79423 0.9819178 0.1828293
#> 613 simple_ma exponential_ma 0.2008547 15.25594 0.9831074 0.1723193
#> 614 simple_ma seadec 0.2008547 14.76976 0.9841208 0.1587129
#> 615 simple_ma locf 0.2008547 15.78134 0.9818486 0.1983506
#> 616 simple_ma stl 0.2008547 14.77889 0.9841000 0.1581444
#> 617 simple_ma auto.arima 0.2008547 19.33367 0.9729106 0.1884275
#> 618 simple_ma StructTS 0.2008547 19.34696 0.9728994 0.1889582
#> 619 simple_ma linear_i 0.2008547 19.37331 0.9728253 0.1885916
#> 620 simple_ma spline_i 0.2008547 22.83220 0.9626676 0.2138851
#> 621 simple_ma stine_i 0.2008547 20.08060 0.9707861 0.1874994
#> 622 simple_ma simple_ma 0.2008547 21.07863 0.9678339 0.2486975
#> 623 simple_ma linear_ma 0.2008547 20.54417 0.9694518 0.2296322
#> 624 simple_ma exponential_ma 0.2008547 20.38961 0.9698988 0.2173954
#> 625 simple_ma seadec 0.2008547 19.34696 0.9728994 0.1889582
#> 626 simple_ma locf 0.2008547 33.03938 0.9220415 0.3063395
#> 627 simple_ma stl 0.2008547 19.37331 0.9728253 0.1885916
#> 628 simple_ma auto.arima 0.2008547 20.00337 0.9710585 0.1947507
#> 629 simple_ma StructTS 0.2008547 19.87124 0.9714224 0.1948116
#> 630 simple_ma linear_i 0.2008547 19.88053 0.9713883 0.1936362
#> 631 simple_ma spline_i 0.2008547 22.76920 0.9623168 0.2131155
#> 632 simple_ma stine_i 0.2008547 21.57645 0.9661611 0.2020728
#> 633 simple_ma simple_ma 0.2008547 25.60573 0.9523120 0.2682128
#> 634 simple_ma linear_ma 0.2008547 25.04675 0.9543528 0.2533020
#> 635 simple_ma exponential_ma 0.2008547 24.91566 0.9548148 0.2458567
#> 636 simple_ma seadec 0.2008547 19.87124 0.9714224 0.1948116
#> 637 simple_ma locf 0.2008547 29.66286 0.9371175 0.2922815
#> 638 simple_ma stl 0.2008547 19.88053 0.9713883 0.1936362
#> 639 simple_ma auto.arima 0.2008547 54.31853 0.8188654 0.6980861
#> 640 simple_ma StructTS 0.2008547 14.93931 0.9838091 0.1790477
#> 641 simple_ma linear_i 0.2008547 14.62738 0.9844796 0.1727423
#> 642 simple_ma spline_i 0.2008547 15.79051 0.9818422 0.2030736
#> 643 simple_ma stine_i 0.2008547 14.42818 0.9849107 0.1683164
#> 644 simple_ma simple_ma 0.2008547 17.88223 0.9767923 0.2269950
#> 645 simple_ma linear_ma 0.2008547 16.83281 0.9794440 0.2124645
#> 646 simple_ma exponential_ma 0.2008547 16.04214 0.9813305 0.2006690
#> 647 simple_ma seadec 0.2008547 14.93931 0.9838091 0.1790477
#> 648 simple_ma locf 0.2008547 22.62803 0.9627818 0.2515969
#> 649 simple_ma stl 0.2008547 14.62738 0.9844796 0.1727423
#> 650 simple_ma auto.arima 0.2008547 15.42437 0.9828776 0.1583224
#> 651 simple_ma StructTS 0.2008547 15.38410 0.9829488 0.1579018
#> 652 simple_ma linear_i 0.2008547 15.37616 0.9829667 0.1577721
#> 653 simple_ma spline_i 0.2008547 15.66024 0.9823265 0.1649478
#> 654 simple_ma stine_i 0.2008547 15.18536 0.9834250 0.1592203
#> 655 simple_ma simple_ma 0.2008547 18.54111 0.9750311 0.2195447
#> 656 simple_ma linear_ma 0.2008547 17.47888 0.9778443 0.2001651
#> 657 simple_ma exponential_ma 0.2008547 16.73568 0.9797109 0.1850200
#> 658 simple_ma seadec 0.2008547 15.38410 0.9829488 0.1579018
#> 659 simple_ma locf 0.2008547 19.19197 0.9731593 0.2189590
#> 660 simple_ma stl 0.2008547 15.37616 0.9829667 0.1577721
#> 661 linear_ma auto.arima 0.2008547 30.85194 0.9357911 0.3663335
#> 662 linear_ma StructTS 0.2008547 12.97169 0.9879066 0.1501635
#> 663 linear_ma linear_i 0.2008547 12.90233 0.9880366 0.1494624
#> 664 linear_ma spline_i 0.2008547 17.33380 0.9783454 0.1909692
#> 665 linear_ma stine_i 0.2008547 12.48214 0.9888177 0.1463397
#> 666 linear_ma simple_ma 0.2008547 16.62378 0.9800493 0.2070746
#> 667 linear_ma linear_ma 0.2008547 15.12553 0.9835003 0.1850137
#> 668 linear_ma exponential_ma 0.2008547 14.14236 0.9855747 0.1723964
#> 669 linear_ma seadec 0.2008547 12.97169 0.9879066 0.1501635
#> 670 linear_ma locf 0.2008547 22.42633 0.9642420 0.2362236
#> 671 linear_ma stl 0.2008547 12.90233 0.9880366 0.1494624
#> 672 linear_ma auto.arima 0.2008547 12.29000 0.9890511 0.1364591
#> 673 linear_ma StructTS 0.2008547 12.37203 0.9889013 0.1385700
#> 674 linear_ma linear_i 0.2008547 12.35170 0.9889379 0.1376872
#> 675 linear_ma spline_i 0.2008547 13.88127 0.9860954 0.1567253
#> 676 linear_ma stine_i 0.2008547 12.21895 0.9891758 0.1382427
#> 677 linear_ma simple_ma 0.2008547 15.80933 0.9818820 0.1940939
#> 678 linear_ma linear_ma 0.2008547 14.90879 0.9838871 0.1773734
#> 679 linear_ma exponential_ma 0.2008547 14.29028 0.9851960 0.1659361
#> 680 linear_ma seadec 0.2008547 12.37203 0.9889013 0.1385700
#> 681 linear_ma locf 0.2008547 13.98993 0.9859293 0.1915861
#> 682 linear_ma stl 0.2008547 12.35170 0.9889379 0.1376872
#> 683 linear_ma auto.arima 0.2008547 15.80267 0.9821171 0.1577964
#> 684 linear_ma StructTS 0.2008547 15.72333 0.9822740 0.1568969
#> 685 linear_ma linear_i 0.2008547 15.72333 0.9822740 0.1568969
#> 686 linear_ma spline_i 0.2008547 16.65229 0.9800987 0.1738345
#> 687 linear_ma stine_i 0.2008547 15.71665 0.9823120 0.1606150
#> 688 linear_ma simple_ma 0.2008547 18.70550 0.9749160 0.2344643
#> 689 linear_ma linear_ma 0.2008547 17.49661 0.9780895 0.2095093
#> 690 linear_ma exponential_ma 0.2008547 16.75904 0.9798958 0.1917530
#> 691 linear_ma seadec 0.2008547 15.72333 0.9822740 0.1568969
#> 692 linear_ma locf 0.2008547 22.52338 0.9633739 0.2391503
#> 693 linear_ma stl 0.2008547 15.72333 0.9822740 0.1568969
#> 694 linear_ma auto.arima 0.2008547 15.26100 0.9832371 0.1602600
#> 695 linear_ma StructTS 0.2008547 15.26347 0.9832460 0.1609490
#> 696 linear_ma linear_i 0.2008547 15.26347 0.9832460 0.1609490
#> 697 linear_ma spline_i 0.2008547 15.09222 0.9835631 0.1622069
#> 698 linear_ma stine_i 0.2008547 15.08397 0.9836540 0.1574336
#> 699 linear_ma simple_ma 0.2008547 18.27463 0.9759471 0.2208753
#> 700 linear_ma linear_ma 0.2008547 17.16760 0.9787995 0.2017000
#> 701 linear_ma exponential_ma 0.2008547 16.40581 0.9806531 0.1896753
#> 702 linear_ma seadec 0.2008547 15.26347 0.9832460 0.1609490
#> 703 linear_ma locf 0.2008547 25.89828 0.9517238 0.2506453
#> 704 linear_ma stl 0.2008547 15.26347 0.9832460 0.1609490
#> 705 linear_ma auto.arima 0.2008547 15.47246 0.9826949 0.1727312
#> 706 linear_ma StructTS 0.2008547 15.50432 0.9826098 0.1745578
#> 707 linear_ma linear_i 0.2008547 15.50432 0.9826098 0.1745578
#> 708 linear_ma spline_i 0.2008547 16.05407 0.9813749 0.1853847
#> 709 linear_ma stine_i 0.2008547 15.31586 0.9830439 0.1717336
#> 710 linear_ma simple_ma 0.2008547 18.04566 0.9764182 0.2153529
#> 711 linear_ma linear_ma 0.2008547 16.69178 0.9798287 0.1964834
#> 712 linear_ma exponential_ma 0.2008547 15.70540 0.9821463 0.1826046
#> 713 linear_ma seadec 0.2008547 15.50432 0.9826098 0.1745578
#> 714 linear_ma locf 0.2008547 23.51805 0.9609636 0.2454527
#> 715 linear_ma stl 0.2008547 15.50432 0.9826098 0.1745578
#> 716 linear_ma auto.arima 0.2008547 20.60569 0.9708603 0.2732970
#> 717 linear_ma StructTS 0.2008547 14.09925 0.9856017 0.1574279
#> 718 linear_ma linear_i 0.2008547 14.09925 0.9856017 0.1574279
#> 719 linear_ma spline_i 0.2008547 15.81235 0.9819028 0.1707358
#> 720 linear_ma stine_i 0.2008547 13.88368 0.9860458 0.1556730
#> 721 linear_ma simple_ma 0.2008547 16.57038 0.9802022 0.2050926
#> 722 linear_ma linear_ma 0.2008547 15.51128 0.9826442 0.1871677
#> 723 linear_ma exponential_ma 0.2008547 14.87597 0.9840177 0.1750914
#> 724 linear_ma seadec 0.2008547 14.09925 0.9856017 0.1574279
#> 725 linear_ma locf 0.2008547 15.36868 0.9828821 0.1991564
#> 726 linear_ma stl 0.2008547 14.09925 0.9856017 0.1574279
#> 727 linear_ma auto.arima 0.2008547 19.34450 0.9730583 0.1921276
#> 728 linear_ma StructTS 0.2008547 19.09749 0.9737623 0.1900492
#> 729 linear_ma linear_i 0.2008547 19.09749 0.9737623 0.1900492
#> 730 linear_ma spline_i 0.2008547 22.45227 0.9641003 0.2118716
#> 731 linear_ma stine_i 0.2008547 19.79344 0.9717940 0.1880975
#> 732 linear_ma simple_ma 0.2008547 21.03537 0.9681609 0.2564484
#> 733 linear_ma linear_ma 0.2008547 20.44402 0.9699366 0.2359466
#> 734 linear_ma exponential_ma 0.2008547 20.24693 0.9705050 0.2227174
#> 735 linear_ma seadec 0.2008547 19.09749 0.9737623 0.1900492
#> 736 linear_ma locf 0.2008547 32.91130 0.9230699 0.3120122
#> 737 linear_ma stl 0.2008547 19.09749 0.9737623 0.1900492
#> 738 linear_ma auto.arima 0.2008547 19.49705 0.9726299 0.1945528
#> 739 linear_ma StructTS 0.2008547 19.39784 0.9728863 0.1933514
#> 740 linear_ma linear_i 0.2008547 19.39784 0.9728863 0.1933514
#> 741 linear_ma spline_i 0.2008547 22.04593 0.9648422 0.2072282
#> 742 linear_ma stine_i 0.2008547 21.09245 0.9678222 0.2006120
#> 743 linear_ma simple_ma 0.2008547 25.50432 0.9529433 0.2764732
#> 744 linear_ma linear_ma 0.2008547 24.87090 0.9552331 0.2592095
#> 745 linear_ma exponential_ma 0.2008547 24.68567 0.9558843 0.2501053
#> 746 linear_ma seadec 0.2008547 19.39784 0.9728863 0.1933514
#> 747 linear_ma locf 0.2008547 29.52275 0.9381660 0.2980032
#> 748 linear_ma stl 0.2008547 19.39784 0.9728863 0.1933514
#> 749 linear_ma auto.arima 0.2008547 53.47268 0.8247718 0.7048352
#> 750 linear_ma StructTS 0.2008547 14.14277 0.9855666 0.1740246
#> 751 linear_ma linear_i 0.2008547 13.98521 0.9858870 0.1709445
#> 752 linear_ma spline_i 0.2008547 15.07269 0.9835344 0.2021124
#> 753 linear_ma stine_i 0.2008547 13.74551 0.9863769 0.1653562
#> 754 linear_ma simple_ma 0.2008547 17.71437 0.9773360 0.2328320
#> 755 linear_ma linear_ma 0.2008547 16.54736 0.9802336 0.2164023
#> 756 linear_ma exponential_ma 0.2008547 15.65202 0.9823177 0.2029001
#> 757 linear_ma seadec 0.2008547 14.14277 0.9855666 0.1740246
#> 758 linear_ma locf 0.2008547 22.46439 0.9635191 0.2540771
#> 759 linear_ma stl 0.2008547 13.98521 0.9858870 0.1709445
#> 760 linear_ma auto.arima 0.2008547 15.23815 0.9833301 0.1634218
#> 761 linear_ma StructTS 0.2008547 14.92251 0.9840338 0.1578585
#> 762 linear_ma linear_i 0.2008547 14.92251 0.9840338 0.1578585
#> 763 linear_ma spline_i 0.2008547 14.90855 0.9840639 0.1588783
#> 764 linear_ma stine_i 0.2008547 14.66539 0.9846172 0.1572437
#> 765 linear_ma simple_ma 0.2008547 18.46202 0.9753647 0.2262375
#> 766 linear_ma linear_ma 0.2008547 17.30328 0.9783920 0.2050635
#> 767 linear_ma exponential_ma 0.2008547 16.48115 0.9804182 0.1885476
#> 768 linear_ma seadec 0.2008547 14.92251 0.9840338 0.1578585
#> 769 linear_ma locf 0.2008547 18.97535 0.9739032 0.2210747
#> 770 linear_ma stl 0.2008547 14.92251 0.9840338 0.1578585
#> 771 exponential_ma auto.arima 0.2008547 30.34466 0.9380930 0.3652905
#> 772 exponential_ma StructTS 0.2008547 12.65589 0.9885610 0.1464012
#> 773 exponential_ma linear_i 0.2008547 12.65589 0.9885610 0.1464012
#> 774 exponential_ma spline_i 0.2008547 16.97320 0.9793638 0.1863375
#> 775 exponential_ma stine_i 0.2008547 12.14606 0.9894863 0.1415247
#> 776 exponential_ma simple_ma 0.2008547 16.66368 0.9800667 0.2112792
#> 777 exponential_ma linear_ma 0.2008547 15.10325 0.9836417 0.1880514
#> 778 exponential_ma exponential_ma 0.2008547 14.06681 0.9858097 0.1745332
#> 779 exponential_ma seadec 0.2008547 12.65589 0.9885610 0.1464012
#> 780 exponential_ma locf 0.2008547 22.45952 0.9643868 0.2426966
#> 781 exponential_ma stl 0.2008547 12.65589 0.9885610 0.1464012
#> 782 exponential_ma auto.arima 0.2008547 12.11867 0.9894134 0.1349328
#> 783 exponential_ma StructTS 0.2008547 12.19362 0.9892818 0.1364118
#> 784 exponential_ma linear_i 0.2008547 12.19362 0.9892818 0.1364118
#> 785 exponential_ma spline_i 0.2008547 13.14040 0.9876024 0.1487899
#> 786 exponential_ma stine_i 0.2008547 11.88025 0.9898256 0.1342618
#> 787 exponential_ma simple_ma 0.2008547 15.84825 0.9818998 0.1972037
#> 788 exponential_ma linear_ma 0.2008547 14.91843 0.9839618 0.1797534
#> 789 exponential_ma exponential_ma 0.2008547 14.27585 0.9853141 0.1675009
#> 790 exponential_ma seadec 0.2008547 12.19362 0.9892818 0.1364118
#> 791 exponential_ma locf 0.2008547 14.43817 0.9851410 0.2006984
#> 792 exponential_ma stl 0.2008547 12.19362 0.9892818 0.1364118
#> 793 exponential_ma auto.arima 0.2008547 15.26321 0.9833945 0.1535664
#> 794 exponential_ma StructTS 0.2008547 15.19381 0.9835259 0.1529676
#> 795 exponential_ma linear_i 0.2008547 15.19381 0.9835259 0.1529676
#> 796 exponential_ma spline_i 0.2008547 15.79085 0.9821757 0.1628534
#> 797 exponential_ma stine_i 0.2008547 15.10253 0.9837438 0.1547123
#> 798 exponential_ma simple_ma 0.2008547 18.55129 0.9754593 0.2362057
#> 799 exponential_ma linear_ma 0.2008547 17.24252 0.9788347 0.2099791
#> 800 exponential_ma exponential_ma 0.2008547 16.42498 0.9807910 0.1912447
#> 801 exponential_ma seadec 0.2008547 15.19381 0.9835259 0.1529676
#> 802 exponential_ma locf 0.2008547 22.32707 0.9642189 0.2398162
#> 803 exponential_ma stl 0.2008547 15.19381 0.9835259 0.1529676
#> 804 exponential_ma auto.arima 0.2008547 14.76126 0.9844205 0.1567458
#> 805 exponential_ma StructTS 0.2008547 14.76793 0.9844205 0.1574915
#> 806 exponential_ma linear_i 0.2008547 14.76793 0.9844205 0.1574915
#> 807 exponential_ma spline_i 0.2008547 14.36191 0.9852214 0.1538543
#> 808 exponential_ma stine_i 0.2008547 14.53478 0.9849249 0.1521855
#> 809 exponential_ma simple_ma 0.2008547 18.09191 0.9765691 0.2226488
#> 810 exponential_ma linear_ma 0.2008547 16.88772 0.9796139 0.2019771
#> 811 exponential_ma exponential_ma 0.2008547 16.04996 0.9816026 0.1886234
#> 812 exponential_ma seadec 0.2008547 14.76793 0.9844205 0.1574915
#> 813 exponential_ma locf 0.2008547 25.79016 0.9524121 0.2518238
#> 814 exponential_ma stl 0.2008547 14.76793 0.9844205 0.1574915
#> 815 exponential_ma auto.arima 0.2008547 15.14286 0.9835118 0.1686678
#> 816 exponential_ma StructTS 0.2008547 15.22228 0.9833253 0.1719339
#> 817 exponential_ma linear_i 0.2008547 15.22228 0.9833253 0.1719339
#> 818 exponential_ma spline_i 0.2008547 15.48209 0.9827738 0.1789729
#> 819 exponential_ma stine_i 0.2008547 15.02406 0.9837732 0.1690579
#> 820 exponential_ma simple_ma 0.2008547 17.97544 0.9767294 0.2173558
#> 821 exponential_ma linear_ma 0.2008547 16.56142 0.9802494 0.1974268
#> 822 exponential_ma exponential_ma 0.2008547 15.52871 0.9826385 0.1825641
#> 823 exponential_ma seadec 0.2008547 15.22228 0.9833253 0.1719339
#> 824 exponential_ma locf 0.2008547 23.56823 0.9610597 0.2506067
#> 825 exponential_ma stl 0.2008547 15.22228 0.9833253 0.1719339
#> 826 exponential_ma auto.arima 0.2008547 19.91443 0.9729698 0.2691816
#> 827 exponential_ma StructTS 0.2008547 13.56910 0.9867342 0.1546762
#> 828 exponential_ma linear_i 0.2008547 13.56910 0.9867342 0.1546762
#> 829 exponential_ma spline_i 0.2008547 15.12678 0.9835482 0.1631780
#> 830 exponential_ma stine_i 0.2008547 13.29711 0.9872680 0.1519638
#> 831 exponential_ma simple_ma 0.2008547 16.44660 0.9805934 0.2081285
#> 832 exponential_ma linear_ma 0.2008547 15.28374 0.9832342 0.1887723
#> 833 exponential_ma exponential_ma 0.2008547 14.56712 0.9847526 0.1754346
#> 834 exponential_ma seadec 0.2008547 13.56910 0.9867342 0.1546762
#> 835 exponential_ma locf 0.2008547 15.13560 0.9834945 0.2012247
#> 836 exponential_ma stl 0.2008547 13.56910 0.9867342 0.1546762
#> 837 exponential_ma auto.arima 0.2008547 19.40073 0.9730855 0.1925750
#> 838 exponential_ma StructTS 0.2008547 18.88752 0.9745009 0.1890766
#> 839 exponential_ma linear_i 0.2008547 18.88752 0.9745009 0.1890766
#> 840 exponential_ma spline_i 0.2008547 22.20147 0.9651041 0.2090912
#> 841 exponential_ma stine_i 0.2008547 19.57925 0.9725751 0.1867707
#> 842 exponential_ma simple_ma 0.2008547 21.00416 0.9684495 0.2604095
#> 843 exponential_ma linear_ma 0.2008547 20.36538 0.9703531 0.2387559
#> 844 exponential_ma exponential_ma 0.2008547 20.13365 0.9710177 0.2248353
#> 845 exponential_ma seadec 0.2008547 18.88752 0.9745009 0.1890766
#> 846 exponential_ma locf 0.2008547 32.83135 0.9238742 0.3140289
#> 847 exponential_ma stl 0.2008547 18.88752 0.9745009 0.1890766
#> 848 exponential_ma auto.arima 0.2008547 19.12681 0.9737847 0.1920954
#> 849 exponential_ma StructTS 0.2008547 19.03634 0.9740141 0.1909491
#> 850 exponential_ma linear_i 0.2008547 19.03634 0.9740141 0.1909491
#> 851 exponential_ma spline_i 0.2008547 21.55320 0.9665740 0.2012241
#> 852 exponential_ma stine_i 0.2008547 20.71604 0.9691201 0.1965879
#> 853 exponential_ma simple_ma 0.2008547 25.43046 0.9534736 0.2806556
#> 854 exponential_ma linear_ma 0.2008547 24.73600 0.9559620 0.2614842
#> 855 exponential_ma exponential_ma 0.2008547 24.50787 0.9567592 0.2509801
#> 856 exponential_ma seadec 0.2008547 19.03634 0.9740141 0.1909491
#> 857 exponential_ma locf 0.2008547 29.45817 0.9388760 0.3014714
#> 858 exponential_ma stl 0.2008547 19.03634 0.9740141 0.1909491
#> 859 exponential_ma auto.arima 0.2008547 52.83602 0.8294449 0.7036723
#> 860 exponential_ma StructTS 0.2008547 13.48630 0.9869473 0.1678589
#> 861 exponential_ma linear_i 0.2008547 13.47749 0.9869644 0.1676834
#> 862 exponential_ma spline_i 0.2008547 14.60100 0.9846342 0.1994652
#> 863 exponential_ma stine_i 0.2008547 13.17008 0.9875620 0.1600855
#> 864 exponential_ma simple_ma 0.2008547 17.59727 0.9777481 0.2353018
#> 865 exponential_ma linear_ma 0.2008547 16.33043 0.9808479 0.2173282
#> 866 exponential_ma exponential_ma 0.2008547 15.34781 0.9830879 0.2025343
#> 867 exponential_ma seadec 0.2008547 13.48630 0.9869473 0.1678589
#> 868 exponential_ma locf 0.2008547 22.37154 0.9640246 0.2552562
#> 869 exponential_ma stl 0.2008547 13.47749 0.9869644 0.1676834
#> 870 exponential_ma auto.arima 0.2008547 14.60275 0.9847970 0.1562650
#> 871 exponential_ma StructTS 0.2008547 14.56908 0.9848552 0.1559665
#> 872 exponential_ma linear_i 0.2008547 14.56908 0.9848552 0.1559665
#> 873 exponential_ma spline_i 0.2008547 14.37609 0.9852535 0.1518412
#> 874 exponential_ma stine_i 0.2008547 14.26144 0.9855308 0.1539532
#> 875 exponential_ma simple_ma 0.2008547 18.41542 0.9756138 0.2299957
#> 876 exponential_ma linear_ma 0.2008547 17.17142 0.9788270 0.2075724
#> 877 exponential_ma exponential_ma 0.2008547 16.28121 0.9809861 0.1901126
#> 878 exponential_ma seadec 0.2008547 14.56908 0.9848552 0.1559665
#> 879 exponential_ma locf 0.2008547 18.84461 0.9744047 0.2229083
#> 880 exponential_ma stl 0.2008547 14.56908 0.9848552 0.1559665
#> 881 seadec auto.arima 0.2008547 13.97040 0.9863830 0.1574637
#> 882 seadec StructTS 0.2008547 13.17937 0.9879253 0.1503758
#> 883 seadec linear_i 0.2008547 13.17937 0.9879253 0.1503758
#> 884 seadec spline_i 0.2008547 16.68749 0.9805920 0.1799405
#> 885 seadec stine_i 0.2008547 12.69683 0.9887901 0.1469837
#> 886 seadec simple_ma 0.2008547 17.61305 0.9784302 0.2171546
#> 887 seadec linear_ma 0.2008547 15.98466 0.9822390 0.1940391
#> 888 seadec exponential_ma 0.2008547 14.89985 0.9845642 0.1815200
#> 889 seadec seadec 0.2008547 13.17937 0.9879253 0.1503758
#> 890 seadec locf 0.2008547 24.48224 0.9597304 0.2737386
#> 891 seadec stl 0.2008547 13.17937 0.9879253 0.1503758
#> 892 seadec auto.arima 0.2008547 12.17663 0.9896647 0.1245732
#> 893 seadec StructTS 0.2008547 12.31866 0.9894283 0.1259748
#> 894 seadec linear_i 0.2008547 12.31866 0.9894283 0.1259748
#> 895 seadec spline_i 0.2008547 12.31045 0.9894943 0.1237752
#> 896 seadec stine_i 0.2008547 11.99782 0.9899622 0.1246885
#> 897 seadec simple_ma 0.2008547 16.30701 0.9814631 0.1899701
#> 898 seadec linear_ma 0.2008547 15.27923 0.9837291 0.1720864
#> 899 seadec exponential_ma 0.2008547 14.58884 0.9851714 0.1599296
#> 900 seadec seadec 0.2008547 12.31866 0.9894283 0.1259748
#> 901 seadec locf 0.2008547 17.87790 0.9783218 0.2254788
#> 902 seadec stl 0.2008547 12.31866 0.9894283 0.1259748
#> 903 seadec auto.arima 0.2008547 13.56083 0.9872333 0.1237192
#> 904 seadec StructTS 0.2008547 13.69835 0.9869887 0.1251812
#> 905 seadec linear_i 0.2008547 13.69835 0.9869887 0.1251812
#> 906 seadec spline_i 0.2008547 14.22850 0.9859130 0.1260330
#> 907 seadec stine_i 0.2008547 13.49598 0.9873731 0.1230618
#> 908 seadec simple_ma 0.2008547 18.10909 0.9773036 0.2223167
#> 909 seadec linear_ma 0.2008547 16.43366 0.9813407 0.1918185
#> 910 seadec exponential_ma 0.2008547 15.35270 0.9837087 0.1690595
#> 911 seadec seadec 0.2008547 13.69835 0.9869887 0.1251812
#> 912 seadec locf 0.2008547 22.09817 0.9661096 0.2237913
#> 913 seadec stl 0.2008547 13.69835 0.9869887 0.1251812
#> 914 seadec auto.arima 0.2008547 13.17649 0.9879956 0.1267339
#> 915 seadec StructTS 0.2008547 13.53572 0.9873616 0.1346140
#> 916 seadec linear_i 0.2008547 13.53572 0.9873616 0.1346140
#> 917 seadec spline_i 0.2008547 13.48010 0.9874475 0.1375831
#> 918 seadec stine_i 0.2008547 13.31880 0.9877742 0.1289854
#> 919 seadec simple_ma 0.2008547 17.41977 0.9789951 0.2067674
#> 920 seadec linear_ma 0.2008547 15.92989 0.9824701 0.1823401
#> 921 seadec exponential_ma 0.2008547 14.91266 0.9846572 0.1657027
#> 922 seadec seadec 0.2008547 13.53572 0.9873616 0.1346140
#> 923 seadec locf 0.2008547 25.89704 0.9536423 0.2498990
#> 924 seadec stl 0.2008547 13.53572 0.9873616 0.1346140
#> 925 seadec auto.arima 0.2008547 131.68857 0.4080538 2.1577559
#> 926 seadec StructTS 0.2008547 14.71042 0.9848998 0.1543793
#> 927 seadec linear_i 0.2008547 14.71042 0.9848998 0.1543793
#> 928 seadec spline_i 0.2008547 14.26370 0.9858240 0.1411731
#> 929 seadec stine_i 0.2008547 14.34659 0.9856386 0.1490843
#> 930 seadec simple_ma 0.2008547 17.94109 0.9775448 0.2056972
#> 931 seadec linear_ma 0.2008547 16.38496 0.9812671 0.1847964
#> 932 seadec exponential_ma 0.2008547 15.26613 0.9837373 0.1714047
#> 933 seadec seadec 0.2008547 14.71042 0.9848998 0.1543793
#> 934 seadec locf 0.2008547 25.00317 0.9581546 0.2657642
#> 935 seadec stl 0.2008547 14.71042 0.9848998 0.1543793
#> 936 seadec auto.arima 0.2008547 18.34911 0.9779496 0.2264320
#> 937 seadec StructTS 0.2008547 12.20703 0.9896045 0.1290788
#> 938 seadec linear_i 0.2008547 12.20703 0.9896045 0.1290788
#> 939 seadec spline_i 0.2008547 14.39564 0.9856763 0.1454818
#> 940 seadec stine_i 0.2008547 11.83632 0.9902267 0.1245356
#> 941 seadec simple_ma 0.2008547 15.97875 0.9822172 0.1975102
#> 942 seadec linear_ma 0.2008547 14.52336 0.9853045 0.1745455
#> 943 seadec exponential_ma 0.2008547 13.59211 0.9871185 0.1591350
#> 944 seadec seadec 0.2008547 12.20703 0.9896045 0.1290788
#> 945 seadec locf 0.2008547 15.49746 0.9833036 0.2060401
#> 946 seadec stl 0.2008547 12.20703 0.9896045 0.1290788
#> 947 seadec auto.arima 0.2008547 20.67433 0.9704891 0.1773118
#> 948 seadec StructTS 0.2008547 18.46736 0.9764101 0.1733950
#> 949 seadec linear_i 0.2008547 18.46736 0.9764101 0.1733950
#> 950 seadec spline_i 0.2008547 21.91289 0.9669924 0.1841369
#> 951 seadec stine_i 0.2008547 19.13131 0.9746501 0.1697239
#> 952 seadec simple_ma 0.2008547 20.70456 0.9703420 0.2511317
#> 953 seadec linear_ma 0.2008547 19.99844 0.9723481 0.2291618
#> 954 seadec exponential_ma 0.2008547 19.74205 0.9730487 0.2148272
#> 955 seadec seadec 0.2008547 18.46736 0.9764101 0.1733950
#> 956 seadec locf 0.2008547 33.24171 0.9243396 0.3181017
#> 957 seadec stl 0.2008547 18.46736 0.9764101 0.1733950
#> 958 seadec auto.arima 0.2008547 18.84867 0.9752495 0.1691215
#> 959 seadec StructTS 0.2008547 18.25167 0.9768330 0.1725025
#> 960 seadec linear_i 0.2008547 18.25167 0.9768330 0.1725025
#> 961 seadec spline_i 0.2008547 20.76330 0.9699824 0.1717856
#> 962 seadec stine_i 0.2008547 19.95426 0.9722490 0.1781116
#> 963 seadec simple_ma 0.2008547 25.37059 0.9551619 0.2711442
#> 964 seadec linear_ma 0.2008547 24.45753 0.9583169 0.2483555
#> 965 seadec exponential_ma 0.2008547 24.09178 0.9595496 0.2359322
#> 966 seadec seadec 0.2008547 18.25167 0.9768330 0.1725025
#> 967 seadec locf 0.2008547 29.76522 0.9399001 0.2983965
#> 968 seadec stl 0.2008547 18.25167 0.9768330 0.1725025
#> 969 seadec auto.arima 0.2008547 13.64643 0.9870274 0.1545456
#> 970 seadec StructTS 0.2008547 11.88294 0.9901700 0.1406704
#> 971 seadec linear_i 0.2008547 11.88294 0.9901700 0.1406704
#> 972 seadec spline_i 0.2008547 14.11859 0.9861827 0.1844722
#> 973 seadec stine_i 0.2008547 11.45158 0.9908723 0.1312080
#> 974 seadec simple_ma 0.2008547 17.21506 0.9793404 0.2190507
#> 975 seadec linear_ma 0.2008547 15.55687 0.9831393 0.1955035
#> 976 seadec exponential_ma 0.2008547 14.28126 0.9857960 0.1769701
#> 977 seadec seadec 0.2008547 11.88294 0.9901700 0.1406704
#> 978 seadec locf 0.2008547 22.53643 0.9646791 0.2500649
#> 979 seadec stl 0.2008547 11.88294 0.9901700 0.1406704
#> 980 seadec auto.arima 0.2008547 13.39715 0.9875599 0.1277891
#> 981 seadec StructTS 0.2008547 13.81115 0.9867737 0.1380815
#> 982 seadec linear_i 0.2008547 13.81115 0.9867737 0.1380815
#> 983 seadec spline_i 0.2008547 13.46409 0.9874301 0.1230425
#> 984 seadec stine_i 0.2008547 13.35447 0.9876568 0.1340267
#> 985 seadec simple_ma 0.2008547 18.49826 0.9761362 0.2216547
#> 986 seadec linear_ma 0.2008547 17.00087 0.9798611 0.1974420
#> 987 seadec exponential_ma 0.2008547 15.93417 0.9823216 0.1790478
#> 988 seadec seadec 0.2008547 13.81115 0.9867737 0.1380815
#> 989 seadec locf 0.2008547 19.11903 0.9744977 0.2247892
#> 990 seadec stl 0.2008547 13.81115 0.9867737 0.1380815
#> 991 locf auto.arima 0.2008547 56.36292 0.8181861 0.7733093
#> 992 locf StructTS 0.2008547 13.50493 0.9872397 0.1628501
#> 993 locf linear_i 0.2008547 13.50493 0.9872397 0.1628501
#> 994 locf spline_i 0.2008547 16.72545 0.9804865 0.1899222
#> 995 locf stine_i 0.2008547 13.25860 0.9876927 0.1613797
#> 996 locf simple_ma 0.2008547 17.89773 0.9775593 0.2290357
#> 997 locf linear_ma 0.2008547 16.23101 0.9815498 0.2049302
#> 998 locf exponential_ma 0.2008547 15.16353 0.9838906 0.1915347
#> 999 locf seadec 0.2008547 13.50493 0.9872397 0.1628501
#> 1000 locf locf 0.2008547 27.21244 0.9504424 0.3275497
#> 1001 locf stl 0.2008547 13.50493 0.9872397 0.1628501
#> 1002 locf auto.arima 0.2008547 13.80091 0.9866404 0.1570118
#> 1003 locf StructTS 0.2008547 13.97985 0.9862915 0.1588974
#> 1004 locf linear_i 0.2008547 13.97985 0.9862915 0.1588974
#> 1005 locf spline_i 0.2008547 15.39257 0.9834722 0.1832722
#> 1006 locf stine_i 0.2008547 14.02221 0.9862079 0.1599781
#> 1007 locf simple_ma 0.2008547 16.86611 0.9800313 0.2049095
#> 1008 locf linear_ma 0.2008547 16.03890 0.9819434 0.1893677
#> 1009 locf exponential_ma 0.2008547 15.54053 0.9830517 0.1796264
#> 1010 locf seadec 0.2008547 13.97985 0.9862915 0.1588974
#> 1011 locf locf 0.2008547 21.89100 0.9673107 0.2880827
#> 1012 locf stl 0.2008547 13.97985 0.9862915 0.1588974
#> 1013 locf auto.arima 0.2008547 14.80333 0.9847670 0.1513293
#> 1014 locf StructTS 0.2008547 14.73458 0.9848812 0.1498286
#> 1015 locf linear_i 0.2008547 14.73458 0.9848812 0.1498286
#> 1016 locf spline_i 0.2008547 16.42218 0.9810961 0.1885788
#> 1017 locf stine_i 0.2008547 14.84106 0.9846685 0.1556170
#> 1018 locf simple_ma 0.2008547 18.36811 0.9766106 0.2352123
#> 1019 locf linear_ma 0.2008547 16.83911 0.9803780 0.2047319
#> 1020 locf exponential_ma 0.2008547 15.88359 0.9825293 0.1831181
#> 1021 locf seadec 0.2008547 14.73458 0.9848812 0.1498286
#> 1022 locf locf 0.2008547 24.90276 0.9567547 0.2902305
#> 1023 locf stl 0.2008547 14.73458 0.9848812 0.1498286
#> 1024 locf auto.arima 0.2008547 51.79038 0.8404097 0.7185535
#> 1025 locf StructTS 0.2008547 14.14421 0.9860844 0.1535337
#> 1026 locf linear_i 0.2008547 14.14421 0.9860844 0.1535337
#> 1027 locf spline_i 0.2008547 15.15583 0.9840308 0.1783827
#> 1028 locf stine_i 0.2008547 14.11470 0.9861531 0.1531189
#> 1029 locf simple_ma 0.2008547 17.67956 0.9782131 0.2192033
#> 1030 locf linear_ma 0.2008547 16.18080 0.9817850 0.1931008
#> 1031 locf exponential_ma 0.2008547 15.17753 0.9839895 0.1770115
#> 1032 locf seadec 0.2008547 14.14421 0.9860844 0.1535337
#> 1033 locf locf 0.2008547 28.22725 0.9447913 0.2964057
#> 1034 locf stl 0.2008547 14.14421 0.9860844 0.1535337
#> 1035 locf auto.arima 0.2008547 15.08282 0.9840706 0.1749358
#> 1036 locf StructTS 0.2008547 15.07635 0.9840606 0.1726199
#> 1037 locf linear_i 0.2008547 15.07635 0.9840606 0.1726199
#> 1038 locf spline_i 0.2008547 15.79290 0.9825809 0.1891119
#> 1039 locf stine_i 0.2008547 14.95788 0.9843153 0.1712066
#> 1040 locf simple_ma 0.2008547 17.88048 0.9775848 0.2201012
#> 1041 locf linear_ma 0.2008547 16.31228 0.9813385 0.1984084
#> 1042 locf exponential_ma 0.2008547 15.23023 0.9837300 0.1844385
#> 1043 locf seadec 0.2008547 15.07635 0.9840606 0.1726199
#> 1044 locf locf 0.2008547 27.67481 0.9491978 0.3265653
#> 1045 locf stl 0.2008547 15.07635 0.9840606 0.1726199
#> 1046 locf auto.arima 0.2008547 19.33531 0.9754090 0.2606644
#> 1047 locf StructTS 0.2008547 13.55464 0.9871066 0.1616568
#> 1048 locf linear_i 0.2008547 13.55464 0.9871066 0.1616568
#> 1049 locf spline_i 0.2008547 14.84490 0.9846047 0.1608876
#> 1050 locf stine_i 0.2008547 13.38460 0.9874308 0.1616483
#> 1051 locf simple_ma 0.2008547 16.16786 0.9816974 0.2146226
#> 1052 locf linear_ma 0.2008547 14.89528 0.9844599 0.1921991
#> 1053 locf exponential_ma 0.2008547 14.10760 0.9860486 0.1762453
#> 1054 locf seadec 0.2008547 13.55464 0.9871066 0.1616568
#> 1055 locf locf 0.2008547 20.56499 0.9705301 0.2756429
#> 1056 locf stl 0.2008547 13.55464 0.9871066 0.1616568
#> 1057 locf auto.arima 0.2008547 45.21239 0.8754496 0.6218862
#> 1058 locf StructTS 0.2008547 19.14420 0.9744267 0.1967088
#> 1059 locf linear_i 0.2008547 19.14420 0.9744267 0.1967088
#> 1060 locf spline_i 0.2008547 22.70968 0.9640693 0.2316215
#> 1061 locf stine_i 0.2008547 19.94745 0.9721898 0.1998629
#> 1062 locf simple_ma 0.2008547 21.21033 0.9686271 0.2708117
#> 1063 locf linear_ma 0.2008547 20.53079 0.9706223 0.2480741
#> 1064 locf exponential_ma 0.2008547 20.26941 0.9713601 0.2332946
#> 1065 locf seadec 0.2008547 19.14420 0.9744267 0.1967088
#> 1066 locf locf 0.2008547 35.35428 0.9137511 0.3757872
#> 1067 locf stl 0.2008547 19.14420 0.9744267 0.1967088
#> 1068 locf auto.arima 0.2008547 19.60880 0.9731885 0.2058293
#> 1069 locf StructTS 0.2008547 18.95166 0.9749943 0.1963807
#> 1070 locf linear_i 0.2008547 18.95166 0.9749943 0.1963807
#> 1071 locf spline_i 0.2008547 22.40097 0.9648775 0.2351181
#> 1072 locf stine_i 0.2008547 20.67497 0.9700957 0.2048029
#> 1073 locf simple_ma 0.2008547 25.61835 0.9540819 0.2861332
#> 1074 locf linear_ma 0.2008547 24.73200 0.9571890 0.2639805
#> 1075 locf exponential_ma 0.2008547 24.38133 0.9583753 0.2519975
#> 1076 locf seadec 0.2008547 18.95166 0.9749943 0.1963807
#> 1077 locf locf 0.2008547 31.34124 0.9324727 0.3447327
#> 1078 locf stl 0.2008547 18.95166 0.9749943 0.1963807
#> 1079 locf auto.arima 0.2008547 13.87383 0.9865271 0.1688444
#> 1080 locf StructTS 0.2008547 12.22134 0.9895613 0.1551983
#> 1081 locf linear_i 0.2008547 12.22134 0.9895613 0.1551983
#> 1082 locf spline_i 0.2008547 13.48837 0.9872959 0.1895427
#> 1083 locf stine_i 0.2008547 11.95399 0.9900196 0.1489112
#> 1084 locf simple_ma 0.2008547 17.44935 0.9786985 0.2373841
#> 1085 locf linear_ma 0.2008547 15.75137 0.9826587 0.2110942
#> 1086 locf exponential_ma 0.2008547 14.44249 0.9854273 0.1906308
#> 1087 locf seadec 0.2008547 12.22134 0.9895613 0.1551983
#> 1088 locf locf 0.2008547 24.08399 0.9594566 0.2978376
#> 1089 locf stl 0.2008547 12.22134 0.9895613 0.1551983
#> 1090 locf auto.arima 0.2008547 14.62213 0.9851504 0.1651138
#> 1091 locf StructTS 0.2008547 14.56587 0.9852463 0.1636108
#> 1092 locf linear_i 0.2008547 14.56587 0.9852463 0.1636108
#> 1093 locf spline_i 0.2008547 15.14051 0.9840298 0.1674060
#> 1094 locf stine_i 0.2008547 14.27475 0.9858390 0.1637758
#> 1095 locf simple_ma 0.2008547 18.72619 0.9754261 0.2375496
#> 1096 locf linear_ma 0.2008547 17.24612 0.9791849 0.2124764
#> 1097 locf exponential_ma 0.2008547 16.21190 0.9816277 0.1937323
#> 1098 locf seadec 0.2008547 14.56587 0.9852463 0.1636108
#> 1099 locf locf 0.2008547 21.83730 0.9666129 0.2702733
#> 1100 locf stl 0.2008547 14.56587 0.9852463 0.1636108
#> 1101 stl auto.arima 0.2008547 14.00382 0.9864409 0.1592036
#> 1102 stl StructTS 0.2008547 13.21107 0.9879649 0.1521344
#> 1103 stl linear_i 0.2008547 13.21107 0.9879649 0.1521344
#> 1104 stl spline_i 0.2008547 16.75287 0.9806368 0.1796529
#> 1105 stl stine_i 0.2008547 12.63066 0.9890002 0.1490535
#> 1106 stl simple_ma 0.2008547 17.76589 0.9782330 0.2171326
#> 1107 stl linear_ma 0.2008547 16.13142 0.9820545 0.1943271
#> 1108 stl exponential_ma 0.2008547 15.04493 0.9843858 0.1818492
#> 1109 stl seadec 0.2008547 13.21107 0.9879649 0.1521344
#> 1110 stl locf 0.2008547 24.84183 0.9588571 0.2807643
#> 1111 stl stl 0.2008547 13.21107 0.9879649 0.1521344
#> 1112 stl auto.arima 0.2008547 12.44872 0.9892996 0.1278924
#> 1113 stl StructTS 0.2008547 12.59522 0.9890517 0.1291620
#> 1114 stl linear_i 0.2008547 12.59522 0.9890517 0.1291620
#> 1115 stl spline_i 0.2008547 13.13673 0.9881580 0.1335204
#> 1116 stl stine_i 0.2008547 12.61746 0.9890079 0.1324014
#> 1117 stl simple_ma 0.2008547 16.32643 0.9815831 0.1880456
#> 1118 stl linear_ma 0.2008547 15.33057 0.9837654 0.1715409
#> 1119 stl exponential_ma 0.2008547 14.68283 0.9851151 0.1605483
#> 1120 stl seadec 0.2008547 12.59522 0.9890517 0.1291620
#> 1121 stl locf 0.2008547 18.42946 0.9771753 0.2310448
#> 1122 stl stl 0.2008547 12.59522 0.9890517 0.1291620
#> 1123 stl auto.arima 0.2008547 14.12693 0.9862117 0.1329277
#> 1124 stl StructTS 0.2008547 13.67427 0.9871335 0.1276131
#> 1125 stl linear_i 0.2008547 13.67427 0.9871335 0.1276131
#> 1126 stl spline_i 0.2008547 14.44258 0.9856028 0.1290475
#> 1127 stl stine_i 0.2008547 13.47879 0.9874941 0.1262945
#> 1128 stl simple_ma 0.2008547 17.89182 0.9780544 0.2174197
#> 1129 stl linear_ma 0.2008547 16.23412 0.9819570 0.1875294
#> 1130 stl exponential_ma 0.2008547 15.17440 0.9842239 0.1646331
#> 1131 stl seadec 0.2008547 13.67427 0.9871335 0.1276131
#> 1132 stl locf 0.2008547 21.90489 0.9670449 0.2203125
#> 1133 stl stl 0.2008547 13.67427 0.9871335 0.1276131
#> 1134 stl auto.arima 0.2008547 13.55713 0.9873961 0.1371181
#> 1135 stl StructTS 0.2008547 13.59315 0.9873468 0.1379991
#> 1136 stl linear_i 0.2008547 13.59315 0.9873468 0.1379991
#> 1137 stl spline_i 0.2008547 13.80139 0.9869384 0.1458506
#> 1138 stl stine_i 0.2008547 13.49453 0.9875321 0.1357278
#> 1139 stl simple_ma 0.2008547 17.50507 0.9789577 0.2046808
#> 1140 stl linear_ma 0.2008547 15.97306 0.9825108 0.1806516
#> 1141 stl exponential_ma 0.2008547 14.94000 0.9847169 0.1646377
#> 1142 stl seadec 0.2008547 13.59315 0.9873468 0.1379991
#> 1143 stl locf 0.2008547 25.92435 0.9540203 0.2476965
#> 1144 stl stl 0.2008547 13.59315 0.9873468 0.1379991
#> 1145 stl auto.arima 0.2008547 14.94648 0.9845624 0.1622514
#> 1146 stl StructTS 0.2008547 14.96144 0.9845285 0.1625789
#> 1147 stl linear_i 0.2008547 14.96144 0.9845285 0.1625789
#> 1148 stl spline_i 0.2008547 14.74437 0.9850022 0.1555275
#> 1149 stl stine_i 0.2008547 14.70506 0.9850577 0.1608047
#> 1150 stl simple_ma 0.2008547 17.95277 0.9777290 0.2038778
#> 1151 stl linear_ma 0.2008547 16.43290 0.9813353 0.1848547
#> 1152 stl exponential_ma 0.2008547 15.36206 0.9836882 0.1729916
#> 1153 stl seadec 0.2008547 14.96144 0.9845285 0.1625789
#> 1154 stl locf 0.2008547 25.34006 0.9574180 0.2749592
#> 1155 stl stl 0.2008547 14.96144 0.9845285 0.1625789
#> 1156 stl auto.arima 0.2008547 40.98095 0.9010672 0.5287391
#> 1157 stl StructTS 0.2008547 12.45708 0.9892849 0.1350112
#> 1158 stl linear_i 0.2008547 12.45708 0.9892849 0.1350112
#> 1159 stl spline_i 0.2008547 14.89147 0.9848886 0.1501063
#> 1160 stl stine_i 0.2008547 12.14218 0.9898199 0.1316771
#> 1161 stl simple_ma 0.2008547 16.04001 0.9822324 0.1971819
#> 1162 stl linear_ma 0.2008547 14.61806 0.9852372 0.1760885
#> 1163 stl exponential_ma 0.2008547 13.73218 0.9869639 0.1612915
#> 1164 stl seadec 0.2008547 12.45708 0.9892849 0.1350112
#> 1165 stl locf 0.2008547 15.66885 0.9831242 0.2102385
#> 1166 stl stl 0.2008547 12.45708 0.9892849 0.1350112
#> 1167 stl auto.arima 0.2008547 18.42125 0.9767150 0.1752017
#> 1168 stl StructTS 0.2008547 18.49435 0.9765511 0.1752473
#> 1169 stl linear_i 0.2008547 18.49435 0.9765511 0.1752473
#> 1170 stl spline_i 0.2008547 22.03189 0.9668838 0.1916896
#> 1171 stl stine_i 0.2008547 19.24141 0.9745776 0.1746717
#> 1172 stl simple_ma 0.2008547 20.69922 0.9706165 0.2499269
#> 1173 stl linear_ma 0.2008547 19.98940 0.9726164 0.2281578
#> 1174 stl exponential_ma 0.2008547 19.73982 0.9732936 0.2143970
#> 1175 stl seadec 0.2008547 18.49435 0.9765511 0.1752473
#> 1176 stl locf 0.2008547 33.49188 0.9238489 0.3228492
#> 1177 stl stl 0.2008547 18.49435 0.9765511 0.1752473
#> 1178 stl auto.arima 0.2008547 18.76455 0.9756975 0.1707342
#> 1179 stl StructTS 0.2008547 18.22207 0.9771119 0.1741292
#> 1180 stl linear_i 0.2008547 18.22207 0.9771119 0.1741292
#> 1181 stl spline_i 0.2008547 20.60254 0.9707214 0.1709846
#> 1182 stl stine_i 0.2008547 19.96782 0.9724623 0.1823911
#> 1183 stl simple_ma 0.2008547 25.39398 0.9554923 0.2687157
#> 1184 stl linear_ma 0.2008547 24.47445 0.9586453 0.2469657
#> 1185 stl exponential_ma 0.2008547 24.10781 0.9598750 0.2353610
#> 1186 stl seadec 0.2008547 18.22207 0.9771119 0.1741292
#> 1187 stl locf 0.2008547 29.96833 0.9397444 0.2996513
#> 1188 stl stl 0.2008547 18.22207 0.9771119 0.1741292
#> 1189 stl auto.arima 0.2008547 13.94824 0.9865800 0.1603171
#> 1190 stl StructTS 0.2008547 12.23804 0.9896562 0.1465474
#> 1191 stl linear_i 0.2008547 12.23804 0.9896562 0.1465474
#> 1192 stl spline_i 0.2008547 15.02005 0.9845575 0.1947435
#> 1193 stl stine_i 0.2008547 11.89572 0.9902277 0.1398637
#> 1194 stl simple_ma 0.2008547 17.25485 0.9794282 0.2151900
#> 1195 stl linear_ma 0.2008547 15.66233 0.9830563 0.1933457
#> 1196 stl exponential_ma 0.2008547 14.45862 0.9855624 0.1763692
#> 1197 stl seadec 0.2008547 12.23804 0.9896562 0.1465474
#> 1198 stl locf 0.2008547 22.61250 0.9647647 0.2502277
#> 1199 stl stl 0.2008547 12.23804 0.9896562 0.1465474
#> 1200 stl auto.arima 0.2008547 13.73717 0.9870222 0.1349995
#> 1201 stl StructTS 0.2008547 13.89623 0.9867160 0.1430905
#> 1202 stl linear_i 0.2008547 13.89623 0.9867160 0.1430905
#> 1203 stl spline_i 0.2008547 13.88981 0.9867227 0.1317716
#> 1204 stl stine_i 0.2008547 13.49120 0.9874924 0.1401649
#> 1205 stl simple_ma 0.2008547 18.30312 0.9768501 0.2163940
#> 1206 stl linear_ma 0.2008547 16.84714 0.9804016 0.1936544
#> 1207 stl exponential_ma 0.2008547 15.84089 0.9826822 0.1761524
#> 1208 stl seadec 0.2008547 13.89623 0.9867160 0.1430905
#> 1209 stl locf 0.2008547 19.20398 0.9745188 0.2262862
#> 1210 stl stl 0.2008547 13.89623 0.9867160 0.1430905
#> smape
#> 1 0.01765882
#> 2 0.01431906
#> 3 0.01431906
#> 4 0.01731104
#> 5 0.01405481
#> 6 0.01951093
#> 7 0.01744626
#> 8 0.01628225
#> 9 0.01431906
#> 10 0.02534790
#> 11 0.01431906
#> 12 0.01188814
#> 13 0.01202410
#> 14 0.01202410
#> 15 0.01459715
#> 16 0.01213399
#> 17 0.01767295
#> 18 0.01601607
#> 19 0.01500033
#> 20 0.01202410
#> 21 0.02156707
#> 22 0.01202410
#> 23 0.01206969
#> 24 0.01200398
#> 25 0.01200398
#> 26 0.01369507
#> 27 0.01183963
#> 28 0.02032089
#> 29 0.01739183
#> 30 0.01528942
#> 31 0.01200398
#> 32 0.01997699
#> 33 0.01200398
#> 34 0.01411229
#> 35 0.01416875
#> 36 0.01416875
#> 37 0.01573368
#> 38 0.01394529
#> 39 0.02015330
#> 40 0.01793473
#> 41 0.01647836
#> 42 0.01416875
#> 43 0.02408349
#> 44 0.01416875
#> 45 0.01569219
#> 46 0.01621027
#> 47 0.01621027
#> 48 0.01518404
#> 49 0.01578555
#> 50 0.02047133
#> 51 0.01874043
#> 52 0.01757701
#> 53 0.01621027
#> 54 0.02414597
#> 55 0.01621027
#> 56 0.02801870
#> 57 0.01287774
#> 58 0.01287774
#> 59 0.01556395
#> 60 0.01261040
#> 61 0.01856514
#> 62 0.01659151
#> 63 0.01525553
#> 64 0.01287774
#> 65 0.01999622
#> 66 0.01287774
#> 67 0.01984402
#> 68 0.01885267
#> 69 0.01885267
#> 70 0.02392471
#> 71 0.01832323
#> 72 0.02656472
#> 73 0.02448788
#> 74 0.02303819
#> 75 0.01885267
#> 76 0.02980738
#> 77 0.01885267
#> 78 0.01686785
#> 79 0.01675270
#> 80 0.01675270
#> 81 0.01823164
#> 82 0.01712339
#> 83 0.02502236
#> 84 0.02308174
#> 85 0.02196073
#> 86 0.01675270
#> 87 0.02613356
#> 88 0.01675270
#> 89 0.01941978
#> 90 0.01415804
#> 91 0.01415804
#> 92 0.01920273
#> 93 0.01337367
#> 94 0.02050942
#> 95 0.01837459
#> 96 0.01678222
#> 97 0.01415804
#> 98 0.02376252
#> 99 0.01415804
#> 100 0.01381493
#> 101 0.01407944
#> 102 0.01407944
#> 103 0.01272544
#> 104 0.01380319
#> 105 0.02108749
#> 106 0.01900936
#> 107 0.01745711
#> 108 0.01407944
#> 109 0.02203179
#> 110 0.01407944
#> 111 0.04227355
#> 112 0.01436964
#> 113 0.01436964
#> 114 0.01699998
#> 115 0.01399839
#> 116 0.01985849
#> 117 0.01783451
#> 118 0.01659736
#> 119 0.01436964
#> 120 0.02469510
#> 121 0.01436964
#> 122 0.01173612
#> 123 0.01186143
#> 124 0.01186143
#> 125 0.01404291
#> 126 0.01168809
#> 127 0.01790599
#> 128 0.01618318
#> 129 0.01506091
#> 130 0.01186143
#> 131 0.02100844
#> 132 0.01186143
#> 133 0.01212516
#> 134 0.01209503
#> 135 0.01209503
#> 136 0.01311548
#> 137 0.01191335
#> 138 0.02061869
#> 139 0.01775740
#> 140 0.01558638
#> 141 0.01209503
#> 142 0.01987830
#> 143 0.01209503
#> 144 0.01415457
#> 145 0.01424244
#> 146 0.01424244
#> 147 0.01494488
#> 148 0.01378135
#> 149 0.02049267
#> 150 0.01832973
#> 151 0.01691422
#> 152 0.01424244
#> 153 0.02325687
#> 154 0.01424244
#> 155 0.01535401
#> 156 0.01582062
#> 157 0.01582062
#> 158 0.01471920
#> 159 0.01526667
#> 160 0.02050762
#> 161 0.01869553
#> 162 0.01744512
#> 163 0.01582062
#> 164 0.02325706
#> 165 0.01582062
#> 166 0.02750114
#> 167 0.01268652
#> 168 0.01268652
#> 169 0.01472941
#> 170 0.01233372
#> 171 0.01889199
#> 172 0.01685802
#> 173 0.01536546
#> 174 0.01268652
#> 175 0.01960558
#> 176 0.01268652
#> 177 0.01923439
#> 178 0.01921809
#> 179 0.01921809
#> 180 0.02425927
#> 181 0.01871847
#> 182 0.02649519
#> 183 0.02446488
#> 184 0.02303845
#> 185 0.01921809
#> 186 0.03012902
#> 187 0.01921809
#> 188 0.01730212
#> 189 0.01712166
#> 190 0.01712166
#> 191 0.01871926
#> 192 0.01764368
#> 193 0.02537034
#> 194 0.02340588
#> 195 0.02230034
#> 196 0.01712166
#> 197 0.02608863
#> 198 0.01712166
#> 199 0.01937342
#> 200 0.01417364
#> 201 0.01417364
#> 202 0.01846975
#> 203 0.01329242
#> 204 0.02095235
#> 205 0.01894503
#> 206 0.01734671
#> 207 0.01417364
#> 208 0.02329588
#> 209 0.01417364
#> 210 0.01340726
#> 211 0.01422191
#> 212 0.01422191
#> 213 0.01274619
#> 214 0.01389448
#> 215 0.02126909
#> 216 0.01929210
#> 217 0.01775567
#> 218 0.01422191
#> 219 0.02186987
#> 220 0.01422191
#> 221 0.04154401
#> 222 0.01309202
#> 223 0.01309202
#> 224 0.01578632
#> 225 0.01233502
#> 226 0.01921895
#> 227 0.01719621
#> 228 0.01599160
#> 229 0.01309202
#> 230 0.02281817
#> 231 0.01309202
#> 232 0.01206560
#> 233 0.01221554
#> 234 0.01221554
#> 235 0.01348368
#> 236 0.01159551
#> 237 0.01814617
#> 238 0.01654025
#> 239 0.01552622
#> 240 0.01221554
#> 241 0.01949232
#> 242 0.01221554
#> 243 0.01294118
#> 244 0.01237823
#> 245 0.01237823
#> 246 0.01320743
#> 247 0.01222460
#> 248 0.02090172
#> 249 0.01824617
#> 250 0.01618451
#> 251 0.01237823
#> 252 0.01972963
#> 253 0.01237823
#> 254 0.01350867
#> 255 0.01430481
#> 256 0.01430481
#> 257 0.01365340
#> 258 0.01379721
#> 259 0.02053516
#> 260 0.01853244
#> 261 0.01724352
#> 262 0.01430481
#> 263 0.02248917
#> 264 0.01430481
#> 265 0.01813340
#> 266 0.01573041
#> 267 0.01573041
#> 268 0.01445973
#> 269 0.01503737
#> 270 0.02075129
#> 271 0.01893907
#> 272 0.01764916
#> 273 0.01573041
#> 274 0.02271856
#> 275 0.01573041
#> 276 0.02763004
#> 277 0.01273802
#> 278 0.01273802
#> 279 0.01401077
#> 280 0.01234258
#> 281 0.01913433
#> 282 0.01715800
#> 283 0.01565865
#> 284 0.01273802
#> 285 0.01853127
#> 286 0.01273802
#> 287 0.02273855
#> 288 0.01881398
#> 289 0.01881398
#> 290 0.02398853
#> 291 0.01822641
#> 292 0.02660962
#> 293 0.02453882
#> 294 0.02308019
#> 295 0.01881398
#> 296 0.02842525
#> 297 0.01881398
#> 298 0.01713675
#> 299 0.01686422
#> 300 0.01686422
#> 301 0.01862702
#> 302 0.01712321
#> 303 0.02516821
#> 304 0.02324923
#> 305 0.02213870
#> 306 0.01686422
#> 307 0.02477359
#> 308 0.01686422
#> 309 0.01989707
#> 310 0.01469634
#> 311 0.01469634
#> 312 0.01812952
#> 313 0.01377477
#> 314 0.02129229
#> 315 0.01946987
#> 316 0.01801574
#> 317 0.01469634
#> 318 0.02274492
#> 319 0.01469634
#> 320 0.01346325
#> 321 0.01425435
#> 322 0.01425435
#> 323 0.01264539
#> 324 0.01362529
#> 325 0.02156888
#> 326 0.01952996
#> 327 0.01795046
#> 328 0.01425435
#> 329 0.02077373
#> 330 0.01425435
#> 331 0.04104889
#> 332 0.01302810
#> 333 0.01302810
#> 334 0.01519472
#> 335 0.01250723
#> 336 0.01957153
#> 337 0.01740374
#> 338 0.01603618
#> 339 0.01302810
#> 340 0.02406119
#> 341 0.01302810
#> 342 0.01166378
#> 343 0.01184369
#> 344 0.01184369
#> 345 0.01246412
#> 346 0.01147940
#> 347 0.01799071
#> 348 0.01630710
#> 349 0.01525610
#> 350 0.01184369
#> 351 0.02048374
#> 352 0.01184369
#> 353 0.01243825
#> 354 0.01189461
#> 355 0.01189461
#> 356 0.01241699
#> 357 0.01189501
#> 358 0.02072068
#> 359 0.01793446
#> 360 0.01579215
#> 361 0.01189461
#> 362 0.01955684
#> 363 0.01189461
#> 364 0.01382606
#> 365 0.01393069
#> 366 0.01393069
#> 367 0.01297177
#> 368 0.01349024
#> 369 0.02037572
#> 370 0.01828317
#> 371 0.01695476
#> 372 0.01393069
#> 373 0.02279434
#> 374 0.01393069
#> 375 0.01552550
#> 376 0.01554675
#> 377 0.01554675
#> 378 0.01349237
#> 379 0.01483461
#> 380 0.02066948
#> 381 0.01882115
#> 382 0.01745669
#> 383 0.01554675
#> 384 0.02322051
#> 385 0.01554675
#> 386 0.07256267
#> 387 0.01240474
#> 388 0.01240474
#> 389 0.01388248
#> 390 0.01182283
#> 391 0.01917061
#> 392 0.01706990
#> 393 0.01543741
#> 394 0.01240474
#> 395 0.01888202
#> 396 0.01240474
#> 397 0.01869017
#> 398 0.01867650
#> 399 0.01867650
#> 400 0.02362209
#> 401 0.01816357
#> 402 0.02657244
#> 403 0.02443408
#> 404 0.02292543
#> 405 0.01867650
#> 406 0.02890260
#> 407 0.01867650
#> 408 0.01659516
#> 409 0.01646337
#> 410 0.01646337
#> 411 0.01751347
#> 412 0.01670003
#> 413 0.02523020
#> 414 0.02314972
#> 415 0.02194124
#> 416 0.01646337
#> 417 0.02492686
#> 418 0.01646337
#> 419 0.01901037
#> 420 0.01380796
#> 421 0.01380796
#> 422 0.01816364
#> 423 0.01281943
#> 424 0.02114995
#> 425 0.01906740
#> 426 0.01740350
#> 427 0.01380796
#> 428 0.02273123
#> 429 0.01380796
#> 430 0.01265134
#> 431 0.01403625
#> 432 0.01403625
#> 433 0.01178710
#> 434 0.01354397
#> 435 0.02166843
#> 436 0.01955345
#> 437 0.01797205
#> 438 0.01403625
#> 439 0.02095058
#> 440 0.01403625
#> 441 0.04123272
#> 442 0.01308747
#> 443 0.01308747
#> 444 0.01561174
#> 445 0.01252869
#> 446 0.01926577
#> 447 0.01723274
#> 448 0.01601926
#> 449 0.01308747
#> 450 0.02292308
#> 451 0.01308747
#> 452 0.01200890
#> 453 0.01215375
#> 454 0.01215375
#> 455 0.01334058
#> 456 0.01148961
#> 457 0.01814339
#> 458 0.01652933
#> 459 0.01550628
#> 460 0.01215375
#> 461 0.01951466
#> 462 0.01215375
#> 463 0.01283794
#> 464 0.01227264
#> 465 0.01227264
#> 466 0.01297569
#> 467 0.01214390
#> 468 0.02088833
#> 469 0.01820217
#> 470 0.01612534
#> 471 0.01227264
#> 472 0.01966379
#> 473 0.01227264
#> 474 0.01344145
#> 475 0.01424224
#> 476 0.01424224
#> 477 0.01359333
#> 478 0.01374876
#> 479 0.02050503
#> 480 0.01848662
#> 481 0.01719265
#> 482 0.01424224
#> 483 0.02252656
#> 484 0.01424224
#> 485 0.01793973
#> 486 0.01558615
#> 487 0.01558615
#> 488 0.01424467
#> 489 0.01488403
#> 490 0.02071858
#> 491 0.01888743
#> 492 0.01758687
#> 493 0.01558615
#> 494 0.02267379
#> 495 0.01558615
#> 496 0.02758538
#> 497 0.01260450
#> 498 0.01260450
#> 499 0.01385777
#> 500 0.01219838
#> 501 0.01917340
#> 502 0.01717734
#> 503 0.01565410
#> 504 0.01260450
#> 505 0.01853725
#> 506 0.01260450
#> 507 0.02291555
#> 508 0.01866934
#> 509 0.01866934
#> 510 0.02382616
#> 511 0.01802698
#> 512 0.02658632
#> 513 0.02449929
#> 514 0.02301179
#> 515 0.01866934
#> 516 0.02839757
#> 517 0.01866934
#> 518 0.01705415
#> 519 0.01679521
#> 520 0.01679521
#> 521 0.01853977
#> 522 0.01703841
#> 523 0.02516951
#> 524 0.02324172
#> 525 0.02211419
#> 526 0.01679521
#> 527 0.02471821
#> 528 0.01679521
#> 529 0.01966883
#> 530 0.01446640
#> 531 0.01446640
#> 532 0.01811169
#> 533 0.01348997
#> 534 0.02124951
#> 535 0.01936558
#> 536 0.01788068
#> 537 0.01446640
#> 538 0.02267365
#> 539 0.01446640
#> 540 0.01322367
#> 541 0.01409827
#> 542 0.01409827
#> 543 0.01230219
#> 544 0.01348726
#> 545 0.02154859
#> 546 0.01948096
#> 547 0.01788344
#> 548 0.01409827
#> 549 0.02080720
#> 550 0.01409827
#> 551 0.04526340
#> 552 0.01472265
#> 553 0.01452442
#> 554 0.01815161
#> 555 0.01427142
#> 556 0.01873941
#> 557 0.01699416
#> 558 0.01592231
#> 559 0.01472265
#> 560 0.02166821
#> 561 0.01452442
#> 562 0.01313985
#> 563 0.01366389
#> 564 0.01327525
#> 565 0.01746363
#> 566 0.01361187
#> 567 0.01813573
#> 568 0.01666627
#> 569 0.01576977
#> 570 0.01366389
#> 571 0.01794977
#> 572 0.01327525
#> 573 0.01448412
#> 574 0.01443293
#> 575 0.01439644
#> 576 0.01748282
#> 577 0.01477049
#> 578 0.02141697
#> 579 0.01908275
#> 580 0.01729052
#> 581 0.01443293
#> 582 0.02088918
#> 583 0.01439644
#> 584 0.01623785
#> 585 0.01645703
#> 586 0.01633036
#> 587 0.01683585
#> 588 0.01617911
#> 589 0.02109065
#> 590 0.01945278
#> 591 0.01851532
#> 592 0.01645703
#> 593 0.02335104
#> 594 0.01633036
#> 595 0.01772248
#> 596 0.01775723
#> 597 0.01775723
#> 598 0.01839204
#> 599 0.01732442
#> 600 0.02126513
#> 601 0.01967226
#> 602 0.01848619
#> 603 0.01775723
#> 604 0.02239056
#> 605 0.01775723
#> 606 0.03114214
#> 607 0.01448977
#> 608 0.01441486
#> 609 0.01668847
#> 610 0.01435220
#> 611 0.01901455
#> 612 0.01740127
#> 613 0.01625590
#> 614 0.01448977
#> 615 0.01894128
#> 616 0.01441486
#> 617 0.02041217
#> 618 0.02040852
#> 619 0.02034659
#> 620 0.02678274
#> 621 0.01999278
#> 622 0.02657981
#> 623 0.02475091
#> 624 0.02349920
#> 625 0.02040852
#> 626 0.02906537
#> 627 0.02034659
#> 628 0.01856304
#> 629 0.01859141
#> 630 0.01847783
#> 631 0.02180221
#> 632 0.01913385
#> 633 0.02507193
#> 634 0.02370562
#> 635 0.02295694
#> 636 0.01859141
#> 637 0.02551426
#> 638 0.01847783
#> 639 0.09021990
#> 640 0.01751556
#> 641 0.01694801
#> 642 0.01981623
#> 643 0.01644490
#> 644 0.02184147
#> 645 0.02047194
#> 646 0.01937232
#> 647 0.01751556
#> 648 0.02373808
#> 649 0.01694801
#> 650 0.01582455
#> 651 0.01582479
#> 652 0.01580931
#> 653 0.01604012
#> 654 0.01577276
#> 655 0.02151127
#> 656 0.01981347
#> 657 0.01846491
#> 658 0.01582479
#> 659 0.02153004
#> 660 0.01580931
#> 661 0.04429633
#> 662 0.01412924
#> 663 0.01406933
#> 664 0.01739033
#> 665 0.01371319
#> 666 0.01878722
#> 667 0.01693424
#> 668 0.01581433
#> 669 0.01412924
#> 670 0.02136839
#> 671 0.01406933
#> 672 0.01280502
#> 673 0.01302896
#> 674 0.01293373
#> 675 0.01646288
#> 676 0.01318332
#> 677 0.01813125
#> 678 0.01662964
#> 679 0.01565785
#> 680 0.01302896
#> 681 0.01812221
#> 682 0.01293373
#> 683 0.01389880
#> 684 0.01382791
#> 685 0.01382791
#> 686 0.01620127
#> 687 0.01410845
#> 688 0.02121338
#> 689 0.01878971
#> 690 0.01692770
#> 691 0.01382791
#> 692 0.02033683
#> 693 0.01382791
#> 694 0.01570110
#> 695 0.01577996
#> 696 0.01577996
#> 697 0.01591010
#> 698 0.01552635
#> 699 0.02095623
#> 700 0.01921777
#> 701 0.01817898
#> 702 0.01577996
#> 703 0.02295691
#> 704 0.01577996
#> 705 0.01700170
#> 706 0.01725448
#> 707 0.01725448
#> 708 0.01747286
#> 709 0.01680207
#> 710 0.02111926
#> 711 0.01945438
#> 712 0.01820409
#> 713 0.01725448
#> 714 0.02209178
#> 715 0.01725448
#> 716 0.03022608
#> 717 0.01401124
#> 718 0.01401124
#> 719 0.01569785
#> 720 0.01387306
#> 721 0.01898680
#> 722 0.01730854
#> 723 0.01607170
#> 724 0.01401124
#> 725 0.01849490
#> 726 0.01401124
#> 727 0.02061425
#> 728 0.01997535
#> 729 0.01997535
#> 730 0.02608153
#> 731 0.01955175
#> 732 0.02655795
#> 733 0.02466949
#> 734 0.02336526
#> 735 0.01997535
#> 736 0.02872496
#> 737 0.01997535
#> 738 0.01813749
#> 739 0.01804202
#> 740 0.01804202
#> 741 0.02092570
#> 742 0.01861123
#> 743 0.02506360
#> 744 0.02355625
#> 745 0.02270597
#> 746 0.01804202
#> 747 0.02519700
#> 748 0.01804202
#> 749 0.08848183
#> 750 0.01664763
#> 751 0.01637864
#> 752 0.01923317
#> 753 0.01579883
#> 754 0.02172744
#> 755 0.02024828
#> 756 0.01904154
#> 757 0.01664763
#> 758 0.02326300
#> 759 0.01637864
#> 760 0.01592164
#> 761 0.01539273
#> 762 0.01539273
#> 763 0.01513316
#> 764 0.01520017
#> 765 0.02146761
#> 766 0.01967404
#> 767 0.01825775
#> 768 0.01539273
#> 769 0.02109834
#> 770 0.01539273
#> 771 0.04366540
#> 772 0.01369757
#> 773 0.01369757
#> 774 0.01681472
#> 775 0.01322347
#> 776 0.01886644
#> 777 0.01695779
#> 778 0.01578778
#> 779 0.01369757
#> 780 0.02153934
#> 781 0.01369757
#> 782 0.01254321
#> 783 0.01268298
#> 784 0.01268298
#> 785 0.01569171
#> 786 0.01274534
#> 787 0.01814338
#> 788 0.01660447
#> 789 0.01558015
#> 790 0.01268298
#> 791 0.01847365
#> 792 0.01268298
#> 793 0.01342826
#> 794 0.01337984
#> 795 0.01337984
#> 796 0.01524444
#> 797 0.01351143
#> 798 0.02108220
#> 799 0.01859045
#> 800 0.01667752
#> 801 0.01337984
#> 802 0.02011033
#> 803 0.01337984
#> 804 0.01528015
#> 805 0.01535962
#> 806 0.01535962
#> 807 0.01517212
#> 808 0.01498833
#> 809 0.02084047
#> 810 0.01901553
#> 811 0.01788978
#> 812 0.01535962
#> 813 0.02273338
#> 814 0.01535962
#> 815 0.01643145
#> 816 0.01683793
#> 817 0.01683793
#> 818 0.01677369
#> 819 0.01637908
#> 820 0.02099589
#> 821 0.01928260
#> 822 0.01797373
#> 823 0.01683793
#> 824 0.02206517
#> 825 0.01683793
#> 826 0.02957554
#> 827 0.01366009
#> 828 0.01366009
#> 829 0.01499570
#> 830 0.01344924
#> 831 0.01898503
#> 832 0.01723019
#> 833 0.01592122
#> 834 0.01366009
#> 835 0.01834651
#> 836 0.01366009
#> 837 0.02080291
#> 838 0.01966393
#> 839 0.01966393
#> 840 0.02561091
#> 841 0.01919910
#> 842 0.02655730
#> 843 0.02460404
#> 844 0.02325776
#> 845 0.01966393
#> 846 0.02848684
#> 847 0.01966393
#> 848 0.01777278
#> 849 0.01768384
#> 850 0.01768384
#> 851 0.02033794
#> 852 0.01814664
#> 853 0.02506712
#> 854 0.02343936
#> 855 0.02249903
#> 856 0.01768384
#> 857 0.02504325
#> 858 0.01768384
#> 859 0.08723555
#> 860 0.01593910
#> 861 0.01592404
#> 862 0.01880095
#> 863 0.01520343
#> 864 0.02163415
#> 865 0.02005950
#> 866 0.01877225
#> 867 0.01593910
#> 868 0.02299185
#> 869 0.01592404
#> 870 0.01503657
#> 871 0.01503492
#> 872 0.01503492
#> 873 0.01439700
#> 874 0.01472750
#> 875 0.02146016
#> 876 0.01959070
#> 877 0.01812146
#> 878 0.01503492
#> 879 0.02091907
#> 880 0.01503492
#> 881 0.01781138
#> 882 0.01450147
#> 883 0.01450147
#> 884 0.01687804
#> 885 0.01418101
#> 886 0.02004467
#> 887 0.01800641
#> 888 0.01681467
#> 889 0.01450147
#> 890 0.02515598
#> 891 0.01450147
#> 892 0.01182792
#> 893 0.01195531
#> 894 0.01195531
#> 895 0.01413344
#> 896 0.01203721
#> 897 0.01791561
#> 898 0.01626181
#> 899 0.01518630
#> 900 0.01195531
#> 901 0.02098497
#> 902 0.01195531
#> 903 0.01219984
#> 904 0.01173236
#> 905 0.01173236
#> 906 0.01305083
#> 907 0.01158507
#> 908 0.02061972
#> 909 0.01773391
#> 910 0.01554201
#> 911 0.01173236
#> 912 0.01963759
#> 913 0.01173236
#> 914 0.01362353
#> 915 0.01418304
#> 916 0.01418304
#> 917 0.01482016
#> 918 0.01382695
#> 919 0.02027317
#> 920 0.01811685
#> 921 0.01669894
#> 922 0.01418304
#> 923 0.02345655
#> 924 0.01418304
#> 925 0.40170940
#> 926 0.01596075
#> 927 0.01596075
#> 928 0.01464123
#> 929 0.01530013
#> 930 0.02062250
#> 931 0.01877169
#> 932 0.01749931
#> 933 0.01596075
#> 934 0.02361819
#> 935 0.01596075
#> 936 0.02772708
#> 937 0.01231334
#> 938 0.01231334
#> 939 0.01436382
#> 940 0.01199506
#> 941 0.01870200
#> 942 0.01663598
#> 943 0.01520307
#> 944 0.01231334
#> 945 0.01939624
#> 946 0.01231334
#> 947 0.02185044
#> 948 0.01929466
#> 949 0.01929466
#> 950 0.02441959
#> 951 0.01868688
#> 952 0.02678665
#> 953 0.02475306
#> 954 0.02332323
#> 955 0.01929466
#> 956 0.03046070
#> 957 0.01929466
#> 958 0.01742978
#> 959 0.01706838
#> 960 0.01706838
#> 961 0.01893901
#> 962 0.01756337
#> 963 0.02532390
#> 964 0.02340848
#> 965 0.02232673
#> 966 0.01706838
#> 967 0.02628506
#> 968 0.01706838
#> 969 0.01933807
#> 970 0.01411505
#> 971 0.01411505
#> 972 0.01822237
#> 973 0.01324795
#> 974 0.02086462
#> 975 0.01879826
#> 976 0.01719664
#> 977 0.01411505
#> 978 0.02329005
#> 979 0.01411505
#> 980 0.01310070
#> 981 0.01399246
#> 982 0.01399246
#> 983 0.01251984
#> 984 0.01356636
#> 985 0.02131947
#> 986 0.01927231
#> 987 0.01767660
#> 988 0.01399246
#> 989 0.02201874
#> 990 0.01399246
#> 991 0.10268905
#> 992 0.01449691
#> 993 0.01449691
#> 994 0.01666628
#> 995 0.01427315
#> 996 0.01968367
#> 997 0.01771409
#> 998 0.01654334
#> 999 0.01449691
#> 1000 0.02694176
#> 1001 0.01449691
#> 1002 0.01363683
#> 1003 0.01379945
#> 1004 0.01379945
#> 1005 0.01752673
#> 1006 0.01396692
#> 1007 0.01818741
#> 1008 0.01677244
#> 1009 0.01593913
#> 1010 0.01379945
#> 1011 0.02366040
#> 1012 0.01379945
#> 1013 0.01326940
#> 1014 0.01315706
#> 1015 0.01315706
#> 1016 0.01684143
#> 1017 0.01357267
#> 1018 0.02058295
#> 1019 0.01786630
#> 1020 0.01593709
#> 1021 0.01315706
#> 1022 0.02323986
#> 1023 0.01315706
#> 1024 0.09238050
#> 1025 0.01475521
#> 1026 0.01475521
#> 1027 0.01681756
#> 1028 0.01470706
#> 1029 0.02025965
#> 1030 0.01808261
#> 1031 0.01679719
#> 1032 0.01475521
#> 1033 0.02512776
#> 1034 0.01475521
#> 1035 0.01670880
#> 1036 0.01670539
#> 1037 0.01670539
#> 1038 0.01727159
#> 1039 0.01635105
#> 1040 0.02084717
#> 1041 0.01902554
#> 1042 0.01777823
#> 1043 0.01670539
#> 1044 0.02672015
#> 1045 0.01670539
#> 1046 0.02973214
#> 1047 0.01421279
#> 1048 0.01421279
#> 1049 0.01506281
#> 1050 0.01425074
#> 1051 0.01917260
#> 1052 0.01722175
#> 1053 0.01580528
#> 1054 0.01421279
#> 1055 0.02315871
#> 1056 0.01421279
#> 1057 0.08043175
#> 1058 0.01976558
#> 1059 0.01976558
#> 1060 0.02663399
#> 1061 0.01962324
#> 1062 0.02684801
#> 1063 0.02480327
#> 1064 0.02339243
#> 1065 0.01976558
#> 1066 0.03206954
#> 1067 0.01976558
#> 1068 0.01882778
#> 1069 0.01780051
#> 1070 0.01780051
#> 1071 0.02228237
#> 1072 0.01841580
#> 1073 0.02502308
#> 1074 0.02326120
#> 1075 0.02223519
#> 1076 0.01780051
#> 1077 0.02757793
#> 1078 0.01780051
#> 1079 0.01994416
#> 1080 0.01489498
#> 1081 0.01489498
#> 1082 0.01812034
#> 1083 0.01429351
#> 1084 0.02131026
#> 1085 0.01921504
#> 1086 0.01763758
#> 1087 0.01489498
#> 1088 0.02578817
#> 1089 0.01489498
#> 1090 0.01536096
#> 1091 0.01527024
#> 1092 0.01527024
#> 1093 0.01505475
#> 1094 0.01521046
#> 1095 0.02145196
#> 1096 0.01949575
#> 1097 0.01798039
#> 1098 0.01527024
#> 1099 0.02409776
#> 1100 0.01527024
#> 1101 0.01808580
#> 1102 0.01477077
#> 1103 0.01477077
#> 1104 0.01699073
#> 1105 0.01454068
#> 1106 0.02011295
#> 1107 0.01809842
#> 1108 0.01691808
#> 1109 0.01477077
#> 1110 0.02620128
#> 1111 0.01477077
#> 1112 0.01203178
#> 1113 0.01213278
#> 1114 0.01213278
#> 1115 0.01465074
#> 1116 0.01253486
#> 1117 0.01769141
#> 1118 0.01613800
#> 1119 0.01517448
#> 1120 0.01213278
#> 1121 0.02150534
#> 1122 0.01213278
#> 1123 0.01291653
#> 1124 0.01208562
#> 1125 0.01208562
#> 1126 0.01362014
#> 1127 0.01201706
#> 1128 0.02026513
#> 1129 0.01740977
#> 1130 0.01524875
#> 1131 0.01208562
#> 1132 0.01968078
#> 1133 0.01208562
#> 1134 0.01437038
#> 1135 0.01446541
#> 1136 0.01446541
#> 1137 0.01550088
#> 1138 0.01435609
#> 1139 0.02011170
#> 1140 0.01796209
#> 1141 0.01659166
#> 1142 0.01446541
#> 1143 0.02350751
#> 1144 0.01446541
#> 1145 0.01692136
#> 1146 0.01693355
#> 1147 0.01693355
#> 1148 0.01631016
#> 1149 0.01667661
#> 1150 0.02058877
#> 1151 0.01889094
#> 1152 0.01775166
#> 1153 0.01693355
#> 1154 0.02514617
#> 1155 0.01693355
#> 1156 0.07383956
#> 1157 0.01309373
#> 1158 0.01309373
#> 1159 0.01500994
#> 1160 0.01287229
#> 1161 0.01875080
#> 1162 0.01687501
#> 1163 0.01554174
#> 1164 0.01309373
#> 1165 0.02037246
#> 1166 0.01309373
#> 1167 0.01951148
#> 1168 0.01950427
#> 1169 0.01950427
#> 1170 0.02510751
#> 1171 0.01911562
#> 1172 0.02676470
#> 1173 0.02472394
#> 1174 0.02332078
#> 1175 0.01950427
#> 1176 0.03087568
#> 1177 0.01950427
#> 1178 0.01760505
#> 1179 0.01726470
#> 1180 0.01726470
#> 1181 0.01885501
#> 1182 0.01795220
#> 1183 0.02523872
#> 1184 0.02342112
#> 1185 0.02239477
#> 1186 0.01726470
#> 1187 0.02663514
#> 1188 0.01726470
#> 1189 0.01988199
#> 1190 0.01464559
#> 1191 0.01464559
#> 1192 0.01959266
#> 1193 0.01403626
#> 1194 0.02046488
#> 1195 0.01848478
#> 1196 0.01700734
#> 1197 0.01464559
#> 1198 0.02350836
#> 1199 0.01464559
#> 1200 0.01379801
#> 1201 0.01454761
#> 1202 0.01454761
#> 1203 0.01340378
#> 1204 0.01420333
#> 1205 0.02102935
#> 1206 0.01911828
#> 1207 0.01759383
#> 1208 0.01454761
#> 1209 0.02254563
#> 1210 0.01454761
#>
#> [[4]]
#> start_methods actual_methods mean_na std_na mean_rmse std_rmse
#> 1 StructTS StructTS 0.2008547 0 14.31431 2.334887
#> 2 StructTS auto.arima 0.2008547 0 16.64517 5.041850
#> 3 StructTS exponential_ma 0.2008547 0 16.32155 3.209211
#> 4 StructTS linear_i 0.2008547 0 14.31431 2.334887
#> 5 StructTS linear_ma 0.2008547 0 17.18302 2.949485
#> 6 StructTS locf 0.2008547 0 23.46602 5.446737
#> 7 StructTS seadec 0.2008547 0 14.31431 2.334887
#> 8 StructTS simple_ma 0.2008547 0 18.50842 2.733067
#> 9 StructTS spline_i 0.2008547 0 15.71544 3.182524
#> 10 StructTS stine_i 0.2008547 0 14.24623 2.978609
#> 11 StructTS stl 0.2008547 0 14.31431 2.334887
#> 12 auto.arima StructTS 0.2008547 0 14.24733 2.286111
#> 13 auto.arima auto.arima 0.2008547 0 15.04170 2.373105
#> 14 auto.arima exponential_ma 0.2008547 0 16.23223 3.238287
#> 15 auto.arima linear_i 0.2008547 0 14.24733 2.286111
#> 16 auto.arima linear_ma 0.2008547 0 17.12133 2.983822
#> 17 auto.arima locf 0.2008547 0 23.81492 5.278160
#> 18 auto.arima seadec 0.2008547 0 14.24733 2.286111
#> 19 auto.arima simple_ma 0.2008547 0 18.49253 2.770099
#> 20 auto.arima spline_i 0.2008547 0 15.92459 2.946764
#> 21 auto.arima stine_i 0.2008547 0 14.25174 2.891613
#> 22 auto.arima stl 0.2008547 0 14.24733 2.286111
#> 23 exponential_ma StructTS 0.2008547 0 14.95819 2.343390
#> 24 exponential_ma auto.arima 0.2008547 0 21.35114 12.169215
#> 25 exponential_ma exponential_ma 0.2008547 0 16.71840 3.231488
#> 26 exponential_ma linear_i 0.2008547 0 14.95731 2.344007
#> 27 exponential_ma linear_ma 0.2008547 0 17.46003 2.993934
#> 28 exponential_ma locf 0.2008547 0 22.72244 5.766395
#> 29 exponential_ma seadec 0.2008547 0 14.95819 2.343390
#> 30 exponential_ma simple_ma 0.2008547 0 18.60245 2.790537
#> 31 exponential_ma spline_i 0.2008547 0 16.36070 3.081698
#> 32 exponential_ma stine_i 0.2008547 0 14.97116 2.953972
#> 33 exponential_ma stl 0.2008547 0 14.95731 2.344007
#> 34 linear_i StructTS 0.2008547 0 14.29538 2.362017
#> 35 linear_i auto.arima 0.2008547 0 17.00038 5.111857
#> 36 linear_i exponential_ma 0.2008547 0 16.35793 3.241189
#> 37 linear_i linear_i 0.2008547 0 14.29538 2.362017
#> 38 linear_i linear_ma 0.2008547 0 17.21429 2.986500
#> 39 linear_i locf 0.2008547 0 22.93954 5.563269
#> 40 linear_i seadec 0.2008547 0 14.29538 2.362017
#> 41 linear_i simple_ma 0.2008547 0 18.50870 2.768712
#> 42 linear_i spline_i 0.2008547 0 15.41416 3.224143
#> 43 linear_i stine_i 0.2008547 0 14.17298 3.087952
#> 44 linear_i stl 0.2008547 0 14.29538 2.362017
#> 45 linear_ma StructTS 0.2008547 0 15.34947 2.317293
#> 46 linear_ma auto.arima 0.2008547 0 21.78361 12.247973
#> 47 linear_ma exponential_ma 0.2008547 0 16.92446 3.227462
#> 48 linear_ma linear_i 0.2008547 0 15.32475 2.337702
#> 49 linear_ma linear_ma 0.2008547 0 17.60671 2.998164
#> 50 linear_ma locf 0.2008547 0 22.75984 5.824576
#> 51 linear_ma seadec 0.2008547 0 15.34947 2.317293
#> 52 linear_ma simple_ma 0.2008547 0 18.67454 2.800503
#> 53 linear_ma spline_i 0.2008547 0 16.93054 2.965222
#> 54 linear_ma stine_i 0.2008547 0 15.39980 2.908278
#> 55 linear_ma stl 0.2008547 0 15.32475 2.337702
#> 56 locf StructTS 0.2008547 0 14.98776 2.282095
#> 57 locf auto.arima 0.2008547 0 26.44928 17.350254
#> 58 locf exponential_ma 0.2008547 0 16.64081 3.207862
#> 59 locf linear_i 0.2008547 0 14.98776 2.282095
#> 60 locf linear_ma 0.2008547 0 17.47576 2.957500
#> 61 locf locf 0.2008547 0 26.30901 4.630079
#> 62 locf seadec 0.2008547 0 14.98776 2.282095
#> 63 locf simple_ma 0.2008547 0 18.78641 2.746657
#> 64 locf spline_i 0.2008547 0 16.80734 3.156730
#> 65 locf stine_i 0.2008547 0 15.14302 2.861450
#> 66 locf stl 0.2008547 0 14.98776 2.282095
#> 67 seadec StructTS 0.2008547 0 14.20627 2.348817
#> 68 seadec auto.arima 0.2008547 0 26.94886 36.916610
#> 69 seadec exponential_ma 0.2008547 0 16.26615 3.212293
#> 70 seadec linear_i 0.2008547 0 14.20627 2.348817
#> 71 seadec linear_ma 0.2008547 0 17.15495 2.951794
#> 72 seadec locf 0.2008547 0 23.55184 5.383435
#> 73 seadec seadec 0.2008547 0 14.20627 2.348817
#> 74 seadec simple_ma 0.2008547 0 18.51572 2.734518
#> 75 seadec spline_i 0.2008547 0 15.56248 3.246703
#> 76 seadec stine_i 0.2008547 0 14.15840 2.975276
#> 77 seadec stl 0.2008547 0 14.20627 2.348817
#> 78 simple_ma StructTS 0.2008547 0 15.87972 2.267830
#> 79 simple_ma auto.arima 0.2008547 0 22.30146 12.392108
#> 80 simple_ma exponential_ma 0.2008547 0 17.19363 3.221186
#> 81 simple_ma linear_i 0.2008547 0 15.81224 2.330524
#> 82 simple_ma linear_ma 0.2008547 0 17.80220 3.000973
#> 83 simple_ma locf 0.2008547 0 22.89623 5.861232
#> 84 simple_ma seadec 0.2008547 0 15.87972 2.267830
#> 85 simple_ma simple_ma 0.2008547 0 18.78014 2.809086
#> 86 simple_ma spline_i 0.2008547 0 17.74997 2.818676
#> 87 simple_ma stine_i 0.2008547 0 15.93861 2.872149
#> 88 simple_ma stl 0.2008547 0 15.81224 2.330524
#> 89 spline_i StructTS 0.2008547 0 13.96946 2.384498
#> 90 spline_i auto.arima 0.2008547 0 18.63208 9.288675
#> 91 spline_i exponential_ma 0.2008547 0 16.14406 3.222101
#> 92 spline_i linear_i 0.2008547 0 13.96946 2.384498
#> 93 spline_i linear_ma 0.2008547 0 17.06084 2.950460
#> 94 spline_i locf 0.2008547 0 23.39241 5.431886
#> 95 spline_i seadec 0.2008547 0 13.96946 2.384498
#> 96 spline_i simple_ma 0.2008547 0 18.45412 2.718559
#> 97 spline_i spline_i 0.2008547 0 15.19610 3.295435
#> 98 spline_i stine_i 0.2008547 0 13.84789 3.069059
#> 99 spline_i stl 0.2008547 0 13.96946 2.384498
#> 100 stine_i StructTS 0.2008547 0 14.25269 2.369483
#> 101 stine_i auto.arima 0.2008547 0 16.95130 5.106202
#> 102 stine_i exponential_ma 0.2008547 0 16.33031 3.246107
#> 103 stine_i linear_i 0.2008547 0 14.25269 2.369483
#> 104 stine_i linear_ma 0.2008547 0 17.19297 2.989141
#> 105 stine_i locf 0.2008547 0 22.95177 5.553011
#> 106 stine_i seadec 0.2008547 0 14.25269 2.369483
#> 107 stine_i simple_ma 0.2008547 0 18.49671 2.768906
#> 108 stine_i spline_i 0.2008547 0 15.36613 3.229815
#> 109 stine_i stine_i 0.2008547 0 14.13350 3.089166
#> 110 stine_i stl 0.2008547 0 14.25269 2.369483
#> 111 stl StructTS 0.2008547 0 14.33429 2.265570
#> 112 stl auto.arima 0.2008547 0 17.49353 8.509860
#> 113 stl exponential_ma 0.2008547 0 16.30835 3.182862
#> 114 stl linear_i 0.2008547 0 14.33429 2.265570
#> 115 stl linear_ma 0.2008547 0 17.16935 2.934615
#> 116 stl locf 0.2008547 0 23.73861 5.385130
#> 117 stl seadec 0.2008547 0 14.33429 2.265570
#> 118 stl simple_ma 0.2008547 0 18.51331 2.726925
#> 119 stl spline_i 0.2008547 0 15.93137 3.014101
#> 120 stl stine_i 0.2008547 0 14.36648 2.880842
#> 121 stl stl 0.2008547 0 14.33429 2.265570
#> mean_cor std_cor mean_mase std_mase mean_smape std_smape
#> 1 0.9853393 0.005033023 0.1443847 0.01737997 0.01458110 0.002287977
#> 2 0.9795178 0.013595799 0.1722253 0.06536987 0.01924617 0.009336169
#> 3 0.9807255 0.008536589 0.1802104 0.02449558 0.01774106 0.002759905
#> 4 0.9853393 0.005033023 0.1443847 0.01737997 0.01458110 0.002287977
#> 5 0.9788072 0.008125665 0.1956282 0.02366950 0.01917663 0.002687833
#> 6 0.9601942 0.018262368 0.2503591 0.03535015 0.02330848 0.003144918
#> 7 0.9853393 0.005033023 0.1443847 0.01737997 0.01458110 0.002287977
#> 8 0.9755650 0.007961410 0.2183439 0.02414545 0.02123624 0.002682835
#> 9 0.9821270 0.007698846 0.1531998 0.02524746 0.01627463 0.003481081
#> 10 0.9852523 0.006648782 0.1409593 0.01976845 0.01425306 0.002346143
#> 11 0.9853393 0.005033023 0.1443847 0.01737997 0.01458110 0.002287977
#> 12 0.9855581 0.004884471 0.1405491 0.01584031 0.01454467 0.002169322
#> 13 0.9840350 0.005108429 0.1500054 0.02856083 0.01693864 0.004788904
#> 14 0.9810169 0.008515642 0.1736017 0.02386140 0.01751212 0.002784690
#> 15 0.9855581 0.004884471 0.1405491 0.01584031 0.01454467 0.002169322
#> 16 0.9790524 0.008138950 0.1886507 0.02317799 0.01890744 0.002748538
#> 17 0.9594434 0.017726922 0.2496264 0.03287533 0.02368529 0.003003641
#> 18 0.9855581 0.004884471 0.1405491 0.01584031 0.01454467 0.002169322
#> 19 0.9757212 0.008008132 0.2112424 0.02393001 0.02098785 0.002750052
#> 20 0.9818739 0.007121016 0.1527229 0.02346654 0.01661694 0.003246905
#> 21 0.9853471 0.006425766 0.1383295 0.01704650 0.01429931 0.002141011
#> 22 0.9855581 0.004884471 0.1405491 0.01584031 0.01454467 0.002169322
#> 23 0.9836166 0.005322205 0.1623733 0.01761579 0.01539398 0.002192884
#> 24 0.9612915 0.048549925 0.2492993 0.17408857 0.02717718 0.023145162
#> 25 0.9792759 0.008949348 0.1948363 0.02554216 0.01824807 0.002681496
#> 26 0.9836183 0.005323395 0.1623558 0.01760980 0.01539248 0.002192473
#> 27 0.9775526 0.008524926 0.2091101 0.02494187 0.01953746 0.002645441
#> 28 0.9611892 0.018975579 0.2480531 0.03718291 0.02207094 0.003046867
#> 29 0.9836166 0.005322205 0.1623733 0.01761579 0.01539398 0.002192884
#> 30 0.9746603 0.008321975 0.2299184 0.02511225 0.02136322 0.002656738
#> 31 0.9802251 0.007896523 0.1755608 0.02247806 0.01738392 0.003433045
#> 32 0.9833810 0.006982747 0.1601103 0.01923897 0.01515736 0.002164461
#> 33 0.9836183 0.005323395 0.1623558 0.01760980 0.01539248 0.002192473
#> 34 0.9852392 0.005125354 0.1530152 0.01692199 0.01450879 0.002125448
#> 35 0.9784567 0.013778131 0.1864536 0.06638635 0.01990585 0.009062217
#> 36 0.9804494 0.008700771 0.1941715 0.02513900 0.01794388 0.002635967
#> 37 0.9852392 0.005125354 0.1530152 0.01692199 0.01450879 0.002125448
#> 38 0.9785198 0.008292561 0.2100379 0.02493743 0.01934000 0.002615502
#> 39 0.9613993 0.018198309 0.2571236 0.03537918 0.02224966 0.002892752
#> 40 0.9852392 0.005125354 0.1530152 0.01692199 0.01450879 0.002125448
#> 41 0.9753232 0.008110325 0.2334909 0.02569249 0.02133266 0.002650557
#> 42 0.9826118 0.007727153 0.1572210 0.02697359 0.01579918 0.003529477
#> 43 0.9852309 0.006898620 0.1472043 0.02006983 0.01400820 0.002195387
#> 44 0.9852392 0.005125354 0.1530152 0.01692199 0.01450879 0.002125448
#> 45 0.9826788 0.005381596 0.1653849 0.01735787 0.01580895 0.002186285
#> 46 0.9597542 0.049724300 0.2521815 0.17328200 0.02770842 0.023398456
#> 47 0.9786609 0.009059044 0.1941727 0.02548764 0.01842252 0.002697796
#> 48 0.9827275 0.005420308 0.1649185 0.01743466 0.01576654 0.002195074
#> 49 0.9770545 0.008628264 0.2073869 0.02484135 0.01964823 0.002661624
#> 50 0.9607773 0.019249578 0.2447382 0.03808192 0.02216543 0.003144529
#> 51 0.9826788 0.005381596 0.1653849 0.01735787 0.01580895 0.002186285
#> 52 0.9743220 0.008413607 0.2268945 0.02480578 0.02140107 0.002662155
#> 53 0.9787921 0.007853415 0.1819947 0.02050458 0.01805088 0.003324986
#> 54 0.9823660 0.007056174 0.1641347 0.01864130 0.01563684 0.002132486
#> 55 0.9827275 0.005420308 0.1649185 0.01743466 0.01576654 0.002195074
#> 56 0.9839893 0.005118093 0.1671285 0.01671873 0.01548581 0.002026392
#> 57 0.9409798 0.067982215 0.3397478 0.25625978 0.04029814 0.036243778
#> 58 0.9800030 0.008638690 0.1961630 0.02560116 0.01800458 0.002668416
#> 59 0.9839893 0.005118093 0.1671285 0.01671873 0.01548581 0.002026392
#> 60 0.9781110 0.008242981 0.2118363 0.02483973 0.01934580 0.002642333
#> 61 0.9511320 0.017538961 0.3093108 0.03345731 0.02583820 0.002709287
#> 62 0.9839893 0.005118093 0.1671285 0.01671873 0.01548581 0.002026392
#> 63 0.9748530 0.008083899 0.2354963 0.02524240 0.02133668 0.002651616
#> 64 0.9796544 0.008221649 0.1913844 0.02424436 0.01822778 0.003573911
#> 65 0.9834612 0.006708114 0.1680301 0.01910646 0.01546646 0.002041651
#> 66 0.9839893 0.005118093 0.1671285 0.01671873 0.01548581 0.002026392
#> 67 0.9856395 0.005002029 0.1444253 0.01782300 0.01451168 0.002383759
#> 68 0.9257606 0.182018767 0.3545446 0.63439389 0.05566181 0.121689618
#> 69 0.9809673 0.008457898 0.1813529 0.02488104 0.01774675 0.002834234
#> 70 0.9856395 0.005002029 0.1444253 0.01782300 0.01451168 0.002383759
#> 71 0.9790016 0.008063462 0.1970089 0.02403365 0.01917588 0.002765792
#> 72 0.9602679 0.017848127 0.2536064 0.03577443 0.02343041 0.003320646
#> 73 0.9856395 0.005002029 0.1444253 0.01782300 0.01451168 0.002383759
#> 74 0.9756935 0.007915793 0.2202398 0.02446924 0.02124723 0.002753038
#> 75 0.9825535 0.007780613 0.1517424 0.02568121 0.01619883 0.003575383
#> 76 0.9855193 0.006570961 0.1410410 0.01958248 0.01419900 0.002368294
#> 77 0.9856395 0.005002029 0.1444253 0.01782300 0.01451168 0.002383759
#> 78 0.9814005 0.005414594 0.1674420 0.01669868 0.01638638 0.002163010
#> 79 0.9578733 0.051265851 0.2513480 0.17109182 0.02830095 0.023852930
#> 80 0.9778799 0.009182699 0.1911680 0.02498552 0.01865334 0.002707629
#> 81 0.9815360 0.005544644 0.1658348 0.01695669 0.01622803 0.002194191
#> 82 0.9764260 0.008742464 0.2029873 0.02431457 0.01980114 0.002673228
#> 83 0.9600566 0.019518504 0.2410994 0.03776606 0.02250378 0.003198182
#> 84 0.9814005 0.005414594 0.1674420 0.01669868 0.01638638 0.002163010
#> 85 0.9738926 0.008510874 0.2207274 0.02411016 0.02146669 0.002666980
#> 86 0.9766746 0.007794134 0.1879665 0.01851879 0.01894557 0.003224892
#> 87 0.9810586 0.007176829 0.1662600 0.01799356 0.01618538 0.002118007
#> 88 0.9815360 0.005544644 0.1658348 0.01695669 0.01622803 0.002194191
#> 89 0.9861119 0.004996074 0.1460992 0.01688127 0.01416327 0.002177624
#> 90 0.9725410 0.028602900 0.2050398 0.13478352 0.02340122 0.019273784
#> 91 0.9812608 0.008408482 0.1880013 0.02467452 0.01771755 0.002657626
#> 92 0.9861119 0.004996074 0.1460992 0.01688127 0.01416327 0.002177624
#> 93 0.9792507 0.007996625 0.2048237 0.02429820 0.01920242 0.002621636
#> 94 0.9608008 0.017820178 0.2584120 0.03525879 0.02265099 0.002943346
#> 95 0.9861119 0.004996074 0.1460992 0.01688127 0.01416327 0.002177624
#> 96 0.9758853 0.007817658 0.2294458 0.02530233 0.02131198 0.002655450
#> 97 0.9833472 0.007694340 0.1462064 0.02887090 0.01515087 0.003674807
#> 98 0.9861084 0.006625684 0.1412333 0.01919252 0.01372563 0.002215693
#> 99 0.9861119 0.004996074 0.1460992 0.01688127 0.01416327 0.002177624
#> 100 0.9853215 0.005130044 0.1516616 0.01678988 0.01439760 0.002108432
#> 101 0.9785681 0.013703933 0.1847884 0.06614647 0.01979083 0.009028028
#> 102 0.9805091 0.008705654 0.1935217 0.02508580 0.01789746 0.002623595
#> 103 0.9853215 0.005130044 0.1516616 0.01678988 0.01439760 0.002108432
#> 104 0.9785684 0.008295057 0.2095773 0.02490286 0.01931032 0.002605521
#> 105 0.9613648 0.018172661 0.2571389 0.03517517 0.02224358 0.002883085
#> 106 0.9853215 0.005130044 0.1516616 0.01678988 0.01439760 0.002108432
#> 107 0.9753516 0.008109875 0.2332759 0.02566161 0.02132484 0.002640301
#> 108 0.9827113 0.007723696 0.1553623 0.02743763 0.01564036 0.003564813
#> 109 0.9853078 0.006889129 0.1459342 0.01975327 0.01390360 0.002157184
#> 110 0.9853215 0.005130044 0.1516616 0.01678988 0.01439760 0.002108432
#> 111 0.9855345 0.004821500 0.1483513 0.01738131 0.01494441 0.002360369
#> 112 0.9760993 0.026754476 0.1889385 0.12058132 0.02189619 0.018456251
#> 113 0.9810507 0.008331153 0.1808231 0.02477065 0.01775431 0.002847672
#> 114 0.9855345 0.004821500 0.1483513 0.01738131 0.01494441 0.002360369
#> 115 0.9791580 0.007963081 0.1957116 0.02374024 0.01911224 0.002780902
#> 116 0.9600516 0.017869091 0.2564030 0.03700000 0.02399783 0.003350219
#> 117 0.9855345 0.004821500 0.1483513 0.01738131 0.01494441 0.002360369
#> 118 0.9759177 0.007838034 0.2178565 0.02429050 0.02110184 0.002782340
#> 119 0.9820112 0.007295755 0.1582895 0.02463767 0.01690416 0.003533362
#> 120 0.9852672 0.006382087 0.1473050 0.01918751 0.01483050 0.002353924
#> 121 0.9855345 0.004821500 0.1483513 0.01738131 0.01494441 0.002360369
#>
#> [[5]]
#> Time Series:
#> Start = 1
#> End = 468
#> Frequency = 1
#> [1] 112.0000 118.0000 132.0000 122.5475 121.3371 135.0000 148.0000 148.0000
#> [9] 136.0000 119.0000 104.0000 118.0000 115.0000 129.5861 141.0000 135.0000
#> [17] 125.0000 149.0000 170.0000 170.0000 158.0000 133.0000 114.0000 140.0000
#> [25] 145.0000 150.0000 178.0000 163.0000 172.0000 178.0000 199.0000 199.0000
#> [33] 184.0000 162.0000 146.0000 166.0000 171.0000 180.0000 193.0000 188.3008
#> [41] 183.0000 218.0000 230.0000 242.0000 209.0000 191.0000 170.2264 188.2115
#> [49] 196.0000 196.0000 236.0000 235.0000 229.0000 243.0000 264.0000 267.0333
#> [57] 237.0000 211.0000 180.0000 201.0000 204.0000 201.2483 235.0000 227.0000
#> [65] 234.0000 261.3993 286.6311 293.0000 259.0000 232.5730 203.0000 229.0000
#> [73] 242.0000 233.0000 267.0000 269.0000 270.0000 315.0000 344.7909 347.0000
#> [81] 312.0000 274.0000 237.0000 267.0282 284.0000 277.0000 317.0000 313.0000
#> [89] 318.0000 369.3633 413.0000 405.0000 355.9361 306.0000 275.6152 306.0000
#> [97] 315.0000 314.1850 356.0000 355.5381 367.5383 422.0000 470.9198 467.0000
#> [105] 404.0000 347.0000 305.0000 336.0000 340.0000 318.0000 350.7743 348.0000
#> [113] 363.0000 435.0000 491.0000 473.3514 404.0000 359.0000 310.0000 337.0000
#> [121] 360.0000 367.8909 406.0000 396.0000 420.0000 476.1725 548.0000 524.9613
#> [129] 448.8126 407.0000 362.0000 428.8640 338.2155 391.0000 419.0000 461.0000
#> [137] 485.6022 535.0000 622.0000 606.0000 508.0000 461.0000 390.0000 432.0000
#> [145] 112.0000 118.0000 132.0000 131.5030 118.7005 135.0000 148.0000 148.0000
#> [153] 136.0000 119.0000 104.0000 118.0000 115.0000 110.9221 141.0000 135.0000
#> [161] 125.0000 149.0000 170.0000 170.0000 158.0000 133.0000 114.0000 140.0000
#> [169] 145.0000 150.0000 178.0000 163.0000 172.0000 178.0000 199.0000 199.0000
#> [177] 184.0000 162.0000 146.0000 166.0000 171.0000 180.0000 193.0000 188.3008
#> [185] 183.0000 218.0000 230.0000 242.0000 209.0000 191.0000 170.2264 188.2115
#> [193] 196.0000 196.0000 236.0000 235.0000 229.0000 243.0000 264.0000 267.0333
#> [201] 237.0000 211.0000 180.0000 201.0000 204.0000 201.2483 235.0000 227.0000
#> [209] 234.0000 261.3993 286.6311 293.0000 259.0000 232.5730 203.0000 229.0000
#> [217] 242.0000 233.0000 267.0000 269.0000 270.0000 315.0000 344.7909 347.0000
#> [225] 312.0000 274.0000 237.0000 267.0282 284.0000 277.0000 317.0000 313.0000
#> [233] 318.0000 369.3633 413.0000 405.0000 355.9361 306.0000 275.6152 306.0000
#> [241] 315.0000 314.1850 356.0000 355.5381 367.5383 422.0000 470.9198 467.0000
#> [249] 404.0000 347.0000 305.0000 336.0000 340.0000 318.0000 350.7743 348.0000
#> [257] 363.0000 435.0000 491.0000 473.3514 404.0000 359.0000 310.0000 337.0000
#> [265] 360.0000 367.8909 406.0000 396.0000 420.0000 476.1725 548.0000 524.9613
#> [273] 448.8126 407.0000 362.0000 428.8640 338.2155 391.0000 419.0000 461.0000
#> [281] 485.6022 535.0000 622.0000 606.0000 508.0000 461.0000 390.0000 432.0000
#> [289] 112.0000 118.0000 132.0000 131.5030 118.7005 135.0000 148.0000 148.0000
#> [297] 136.0000 119.0000 104.0000 118.0000 115.0000 110.9221 141.0000 135.0000
#> [305] 125.0000 149.0000 170.0000 170.0000 158.0000 133.0000 114.0000 140.0000
#> [313] 145.0000 150.0000 178.0000 163.0000 172.0000 178.0000 199.0000 199.0000
#> [321] 184.0000 162.0000 146.0000 166.0000 171.0000 180.0000 193.0000 188.3008
#> [329] 183.0000 218.0000 230.0000 242.0000 209.0000 191.0000 170.2264 188.2115
#> [337] 196.0000 196.0000 236.0000 235.0000 229.0000 243.0000 264.0000 267.0333
#> [345] 237.0000 211.0000 180.0000 201.0000 204.0000 201.2483 235.0000 227.0000
#> [353] 234.0000 261.3993 286.6311 293.0000 259.0000 232.5730 203.0000 229.0000
#> [361] 242.0000 233.0000 267.0000 269.0000 270.0000 315.0000 344.7909 347.0000
#> [369] 312.0000 274.0000 237.0000 267.0282 284.0000 277.0000 317.0000 313.0000
#> [377] 318.0000 369.3633 413.0000 405.0000 355.9361 306.0000 275.6152 306.0000
#> [385] 315.0000 314.1850 356.0000 355.5381 367.5383 422.0000 470.9198 467.0000
#> [393] 404.0000 347.0000 305.0000 336.0000 340.0000 318.0000 350.7743 348.0000
#> [401] 363.0000 435.0000 491.0000 473.3514 404.0000 359.0000 310.0000 337.0000
#> [409] 360.0000 367.8909 406.0000 396.0000 420.0000 476.1725 548.0000 524.9613
#> [417] 448.8126 407.0000 362.0000 428.8640 338.2155 391.0000 419.0000 461.0000
#> [425] 485.6022 535.0000 622.0000 606.0000 508.0000 461.0000 390.0000 432.0000
#> [433] 112.0000 118.0000 132.0000 131.5030 118.7005 135.0000 148.0000 148.0000
#> [441] 136.0000 119.0000 104.0000 118.0000 115.0000 110.9221 141.0000 135.0000
#> [449] 125.0000 149.0000 170.0000 170.0000 158.0000 133.0000 114.0000 140.0000
#> [457] 145.0000 150.0000 178.0000 163.0000 172.0000 178.0000 199.0000 199.0000
#> [465] 184.0000 162.0000 146.0000 166.0000
#>
# For an easy interpretation of kssa results
# please use function kssa_plot
# }
# Example 2: Compare only locf and linear imputation
library("kssa")
library("imputeTS")
# Create 20% random missing data in tsAirgapComplete time series from imputeTS
airgap_na <- missMethods::delete_MCAR(as.data.frame(tsAirgapComplete), 0.2)
# Convert to time series object
airgap_na_ts <- ts(airgap_na, start = c(1959, 1), end = c(1997, 12), frequency = 12)
# Apply the kssa algorithm with 5 segments, 10 iterations, 20% of missing data,
# compare among all applied methods (locf and linear interpolation).
# Remember that percentmd must match with
# the real percentage of missing data in the input time series
results_kssa <- kssa(airgap_na_ts,
start_methods = c("locf", "linear_i"),
actual_methods = c("locf", "linear_i"),
segments = 5,
iterations = 10,
percentmd = 0.2
)
# Print and check results
results_kssa
#> [[1]]
#> $start_methods
#> [1] "locf" "locf" "locf" "locf" "locf" "locf"
#> [7] "locf" "locf" "locf" "locf" "locf" "locf"
#> [13] "locf" "locf" "locf" "locf" "locf" "locf"
#> [19] "locf" "locf" "linear_i" "linear_i" "linear_i" "linear_i"
#> [25] "linear_i" "linear_i" "linear_i" "linear_i" "linear_i" "linear_i"
#> [31] "linear_i" "linear_i" "linear_i" "linear_i" "linear_i" "linear_i"
#> [37] "linear_i" "linear_i" "linear_i" "linear_i"
#>
#> $actual_methods
#> [1] "locf" "linear_i" "locf" "linear_i" "locf" "linear_i"
#> [7] "locf" "linear_i" "locf" "linear_i" "locf" "linear_i"
#> [13] "locf" "linear_i" "locf" "linear_i" "locf" "linear_i"
#> [19] "locf" "linear_i" "locf" "linear_i" "locf" "linear_i"
#> [25] "locf" "linear_i" "locf" "linear_i" "locf" "linear_i"
#> [31] "locf" "linear_i" "locf" "linear_i" "locf" "linear_i"
#> [37] "locf" "linear_i" "locf" "linear_i"
#>
#> $percent_md
#> [1] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [8] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [15] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [22] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [29] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#> [36] 0.2008547 0.2008547 0.2008547 0.2008547 0.2008547
#>
#> $rmse
#> [1] 25.041376 12.050568 18.959358 13.035029 22.148055 15.215724 23.497227
#> [8] 15.773766 24.584192 13.712013 24.203288 15.087523 26.782999 14.813108
#> [15] 32.321932 21.450776 18.461151 8.244523 18.866886 12.691618 22.214040
#> [22] 11.281992 13.995134 12.357603 17.812350 14.951648 20.801758 15.241303
#> [29] 19.281454 12.496975 20.569759 14.588236 24.601752 14.467713 29.802385
#> [36] 20.808853 14.933467 8.292648 15.488190 11.906723
#>
#> $cor
#> [1] 0.9559549 0.9895928 0.9744403 0.9878325 0.9650902 0.9834647 0.9603129
#> [8] 0.9822195 0.9603025 0.9866679 0.9583245 0.9836163 0.9485011 0.9842834
#> [15] 0.9290482 0.9671176 0.9759712 0.9951113 0.9745508 0.9885411 0.9654108
#> [22] 0.9909896 0.9862175 0.9891396 0.9776917 0.9842142 0.9691951 0.9836141
#> [29] 0.9754749 0.9889680 0.9702322 0.9848512 0.9572118 0.9852438 0.9408069
#> [36] 0.9692649 0.9843348 0.9951106 0.9829887 0.9899469
#>
#> $mase
#> [1] 0.3014284 0.1525749 0.2588599 0.1516824 0.3068743 0.1575972 0.2786466
#> [8] 0.1727699 0.3346482 0.1623169 0.2902644 0.1692604 0.3004300 0.1530438
#> [15] 0.3825717 0.2300422 0.2520526 0.1217755 0.2623997 0.1542389 0.2464857
#> [22] 0.1351027 0.2017238 0.1405486 0.2502071 0.1591931 0.2340359 0.1641171
#> [29] 0.2639125 0.1402460 0.2293464 0.1626648 0.2511752 0.1535733 0.3196872
#> [36] 0.2117986 0.2077293 0.1188559 0.2160191 0.1417739
#>
#> $smape
#> [1] 0.02586256 0.01465303 0.02143332 0.01292897 0.02361962 0.01266959
#> [7] 0.02401851 0.01526792 0.02590890 0.01358427 0.02478647 0.01505461
#> [13] 0.02704595 0.01503666 0.02882496 0.01959450 0.02171255 0.01119344
#> [19] 0.02179181 0.01348903 0.02122420 0.01333677 0.01740955 0.01220903
#> [25] 0.01997418 0.01271150 0.02058105 0.01456026 0.02096426 0.01195275
#> [31] 0.02004065 0.01434877 0.02271850 0.01475277 0.02416268 0.01828170
#> [37] 0.01883585 0.01104369 0.01813921 0.01254811
#>
#> attr(,"row.names")
#> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
#> [26] 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
#> attr(,"class")
#> [1] "kssa.table"
#>
#> [[2]]
#> $start_methods
#> [1] "linear_i" "linear_i" "locf" "locf"
#>
#> $actual_methods
#> [1] "linear_i" "locf" "linear_i" "locf"
#>
#> $mean_na
#> [1] 0.2008547 0.2008547 0.2008547 0.2008547
#>
#> $std_na
#> [1] 0 0 0 0
#>
#> $mean_rmse
#> [1] 13.63937 19.95003 14.20746 23.48665
#>
#> $std_rmse
#> [1] 3.289224 4.836138 3.353331 4.241981
#>
#> $mean_cor
#> [1] 0.9861343 0.9709564 0.9848447 0.9602497
#>
#> $std_cor
#> [1] 0.006934602 0.013963169 0.007293317 0.014182197
#>
#> $mean_mase
#> [1] 0.1527874 0.2420322 0.1625302 0.2968176
#>
#> $std_mase
#> [1] 0.02503855 0.03396453 0.02742438 0.03933161
#>
#> $mean_smape
#> [1] 0.01357453 0.02040501 0.01434720 0.02450047
#>
#> $std_smape
#> [1] 0.002051330 0.002037820 0.002249485 0.002463655
#>
#> attr(,"class")
#> [1] "kssa.table"
#> attr(,"row.names")
#> [1] 1 2 3 4
#> attr(,"groups")
#> # A tibble: 2 × 2
#> start_methods .rows
#> <chr> <list<int>>
#> 1 linear_i [2]
#> 2 locf [2]
#>
#> [[3]]
#> start_methods actual_methods percent_md rmse cor mase
#> 1 locf locf 0.2008547 25.041376 0.9559549 0.3014284
#> 2 locf linear_i 0.2008547 12.050568 0.9895928 0.1525749
#> 3 locf locf 0.2008547 18.959358 0.9744403 0.2588599
#> 4 locf linear_i 0.2008547 13.035029 0.9878325 0.1516824
#> 5 locf locf 0.2008547 22.148055 0.9650902 0.3068743
#> 6 locf linear_i 0.2008547 15.215724 0.9834647 0.1575972
#> 7 locf locf 0.2008547 23.497227 0.9603129 0.2786466
#> 8 locf linear_i 0.2008547 15.773766 0.9822195 0.1727699
#> 9 locf locf 0.2008547 24.584192 0.9603025 0.3346482
#> 10 locf linear_i 0.2008547 13.712013 0.9866679 0.1623169
#> 11 locf locf 0.2008547 24.203288 0.9583245 0.2902644
#> 12 locf linear_i 0.2008547 15.087523 0.9836163 0.1692604
#> 13 locf locf 0.2008547 26.782999 0.9485011 0.3004300
#> 14 locf linear_i 0.2008547 14.813108 0.9842834 0.1530438
#> 15 locf locf 0.2008547 32.321932 0.9290482 0.3825717
#> 16 locf linear_i 0.2008547 21.450776 0.9671176 0.2300422
#> 17 locf locf 0.2008547 18.461151 0.9759712 0.2520526
#> 18 locf linear_i 0.2008547 8.244523 0.9951113 0.1217755
#> 19 locf locf 0.2008547 18.866886 0.9745508 0.2623997
#> 20 locf linear_i 0.2008547 12.691618 0.9885411 0.1542389
#> 21 linear_i locf 0.2008547 22.214040 0.9654108 0.2464857
#> 22 linear_i linear_i 0.2008547 11.281992 0.9909896 0.1351027
#> 23 linear_i locf 0.2008547 13.995134 0.9862175 0.2017238
#> 24 linear_i linear_i 0.2008547 12.357603 0.9891396 0.1405486
#> 25 linear_i locf 0.2008547 17.812350 0.9776917 0.2502071
#> 26 linear_i linear_i 0.2008547 14.951648 0.9842142 0.1591931
#> 27 linear_i locf 0.2008547 20.801758 0.9691951 0.2340359
#> 28 linear_i linear_i 0.2008547 15.241303 0.9836141 0.1641171
#> 29 linear_i locf 0.2008547 19.281454 0.9754749 0.2639125
#> 30 linear_i linear_i 0.2008547 12.496975 0.9889680 0.1402460
#> 31 linear_i locf 0.2008547 20.569759 0.9702322 0.2293464
#> 32 linear_i linear_i 0.2008547 14.588236 0.9848512 0.1626648
#> 33 linear_i locf 0.2008547 24.601752 0.9572118 0.2511752
#> 34 linear_i linear_i 0.2008547 14.467713 0.9852438 0.1535733
#> 35 linear_i locf 0.2008547 29.802385 0.9408069 0.3196872
#> 36 linear_i linear_i 0.2008547 20.808853 0.9692649 0.2117986
#> 37 linear_i locf 0.2008547 14.933467 0.9843348 0.2077293
#> 38 linear_i linear_i 0.2008547 8.292648 0.9951106 0.1188559
#> 39 linear_i locf 0.2008547 15.488190 0.9829887 0.2160191
#> 40 linear_i linear_i 0.2008547 11.906723 0.9899469 0.1417739
#> smape
#> 1 0.02586256
#> 2 0.01465303
#> 3 0.02143332
#> 4 0.01292897
#> 5 0.02361962
#> 6 0.01266959
#> 7 0.02401851
#> 8 0.01526792
#> 9 0.02590890
#> 10 0.01358427
#> 11 0.02478647
#> 12 0.01505461
#> 13 0.02704595
#> 14 0.01503666
#> 15 0.02882496
#> 16 0.01959450
#> 17 0.02171255
#> 18 0.01119344
#> 19 0.02179181
#> 20 0.01348903
#> 21 0.02122420
#> 22 0.01333677
#> 23 0.01740955
#> 24 0.01220903
#> 25 0.01997418
#> 26 0.01271150
#> 27 0.02058105
#> 28 0.01456026
#> 29 0.02096426
#> 30 0.01195275
#> 31 0.02004065
#> 32 0.01434877
#> 33 0.02271850
#> 34 0.01475277
#> 35 0.02416268
#> 36 0.01828170
#> 37 0.01883585
#> 38 0.01104369
#> 39 0.01813921
#> 40 0.01254811
#>
#> [[4]]
#> start_methods actual_methods mean_na std_na mean_rmse std_rmse mean_cor
#> 1 linear_i linear_i 0.2008547 0 13.63937 3.289224 0.9861343
#> 2 linear_i locf 0.2008547 0 19.95003 4.836138 0.9709564
#> 3 locf linear_i 0.2008547 0 14.20746 3.353331 0.9848447
#> 4 locf locf 0.2008547 0 23.48665 4.241981 0.9602497
#> std_cor mean_mase std_mase mean_smape std_smape
#> 1 0.006934602 0.1527874 0.02503855 0.01357453 0.002051330
#> 2 0.013963169 0.2420322 0.03396453 0.02040501 0.002037820
#> 3 0.007293317 0.1625302 0.02742438 0.01434720 0.002249485
#> 4 0.014182197 0.2968176 0.03933161 0.02450047 0.002463655
#>
#> [[5]]
#> Time Series:
#> Start = 1
#> End = 468
#> Frequency = 1
#> [1] 112 118 132 132 132 135 148 148 136 119 104 118 115 115 141 135 125 149
#> [19] 170 170 170 133 114 140 145 150 178 178 172 178 199 199 184 162 146 166
#> [37] 171 180 193 193 183 218 230 242 209 191 191 194 196 196 236 235 229 243
#> [55] 264 264 237 211 180 201 204 204 235 227 234 234 234 293 259 259 203 229
#> [73] 242 233 267 269 270 315 315 315 312 274 237 237 284 277 317 313 318 318
#> [91] 413 405 405 306 306 306 315 315 356 356 356 422 422 467 404 347 305 336
#> [109] 340 318 318 348 363 435 491 491 404 359 310 337 360 342 406 396 420 420
#> [127] 548 548 463 407 362 362 362 391 419 461 461 535 622 606 508 461 390 432
#> [145] 112 118 132 132 132 135 148 148 136 119 104 118 115 115 141 135 125 149
#> [163] 170 170 170 133 114 140 145 150 178 178 172 178 199 199 184 162 146 166
#> [181] 171 180 193 193 183 218 230 242 209 191 191 194 196 196 236 235 229 243
#> [199] 264 264 237 211 180 201 204 204 235 227 234 234 234 293 259 259 203 229
#> [217] 242 233 267 269 270 315 315 315 312 274 237 237 284 277 317 313 318 318
#> [235] 413 405 405 306 306 306 315 315 356 356 356 422 422 467 404 347 305 336
#> [253] 340 318 318 348 363 435 491 491 404 359 310 337 360 342 406 396 420 420
#> [271] 548 548 463 407 362 362 362 391 419 461 461 535 622 606 508 461 390 432
#> [289] 112 118 132 132 132 135 148 148 136 119 104 118 115 115 141 135 125 149
#> [307] 170 170 170 133 114 140 145 150 178 178 172 178 199 199 184 162 146 166
#> [325] 171 180 193 193 183 218 230 242 209 191 191 194 196 196 236 235 229 243
#> [343] 264 264 237 211 180 201 204 204 235 227 234 234 234 293 259 259 203 229
#> [361] 242 233 267 269 270 315 315 315 312 274 237 237 284 277 317 313 318 318
#> [379] 413 405 405 306 306 306 315 315 356 356 356 422 422 467 404 347 305 336
#> [397] 340 318 318 348 363 435 491 491 404 359 310 337 360 342 406 396 420 420
#> [415] 548 548 463 407 362 362 362 391 419 461 461 535 622 606 508 461 390 432
#> [433] 112 118 132 132 132 135 148 148 136 119 104 118 115 115 141 135 125 149
#> [451] 170 170 170 133 114 140 145 150 178 178 172 178 199 199 184 162 146 166
#>
# For an easy interpretation of kssa results
# please use function kssa_plot