Description Usage Arguments Details Value df_models best_forecast df_comparison Examples
select_forecast is the main function of this package. It uses apply_all_models() and other internal functions of this package to generate generate multiple forecasts for the same time series object.
1 2 | select_forecast(x, test_size, horizon, error, dont_apply = "",
verbose = FALSE)
|
x |
A ts object. |
test_size |
The desired length of the test set object to be used to measure the accuracy of the forecast models. |
horizon |
The forecast horizon length |
error |
The accuracy metric to be used to select the best forecast model from apply_all_models(). See error_metrics() for the available metrics. |
dont_apply |
Character vector. Choose one or more models that will not be used on select_forecast(). |
verbose |
logical. Set TRUE if you want mafs to tell you what models are running. |
TODO
A list of three objects:
A data.frame with the accuracy metrics of all models applied to x
A forecast object created by applying the best forecast method to x
A dataframe showing both the forecasted and the observed test set
1 2 3 4 | ## Not run:
select_forecast(austres, 6, 12, "MAPE")
## End(Not run)
|
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