Fit Tidymodels Workflows to Nested Time SeriesSource:
Fits one or more
tidymodels workflow objects to nested time series data using the following process:
Models are iteratively fit to training splits.
Accuracy is calculated on testing splits and is logged. Accuracy results can be retrieved with
Any model that returns an error is logged. Error logs can be retrieved with
Forecast is predicted on testing splits and is logged. Forecast results can be retrieved with
Nested time series data
workflowobjects that will be fit to the nested time series data.
workflowobjects can be provided
yardstick::metric_set()that is used to summarize one or more forecast accuracy (regression) metrics.
An estimated confidence interval based on the calibration data. This is designed to estimate future confidence from out-of-sample prediction error.
Algorithm used to produce confidence intervals. All CI's are Conformal Predictions. Choose one of:
qnorm()to compute quantiles from out-of-sample (test set) residuals.
conformal_split: Uses the split method split conformal inference method described by Lei et al (2018)
Used to control verbosity and parallel processing. See
split_nested_timeseries() for preparing
data for Nested Forecasting. The structure must be a nested data frame, which is suppplied in
Models must be in the form of
tidymodels workflow objects. The models can be provided in two ways:
...(dots): The workflow objects can be provided as dots.
model_listparameter: You can supply one or more workflow objects that are wrapped in a
control object can be provided during fitting to adjust the verbosity and parallel processing.