modeltime_nested_fit: Fit Tidymodels Workflows to Nested Time Series

In modeltime: The Tidymodels Extension for Time Series Modeling

Fit Tidymodels Workflows to Nested Time Series

Description

Fits one or more tidymodels workflow objects to nested time series data using the following process:

1. Models are iteratively fit to training splits.

2. Accuracy is calculated on testing splits and is logged. Accuracy results can be retrieved with extract_nested_test_accuracy()

3. Any model that returns an error is logged. Error logs can be retrieved with extract_nested_error_report()

4. Forecast is predicted on testing splits and is logged. Forecast results can be retrieved with extract_nested_test_forecast()

Usage

modeltime_nested_fit(
  nested_data,
  ...,
  model_list = NULL,
  metric_set = default_forecast_accuracy_metric_set(),
  conf_interval = 0.95,
  conf_method = "conformal_default",
  control = control_nested_fit()
)

Arguments

nested_data	Nested time series data
...	Tidymodels workflow objects that will be fit to the nested time series data.
model_list	Optionally, a list() of Tidymodels workflow objects can be provided
metric_set	A yardstick::metric_set() that is used to summarize one or more forecast accuracy (regression) metrics.
conf_interval	An estimated confidence interval based on the calibration data. This is designed to estimate future confidence from out-of-sample prediction error.
conf_method	Algorithm used to produce confidence intervals. All CI's are Conformal Predictions. Choose one of: conformal_default: Uses 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)
control	Used to control verbosity and parallel processing. See control_nested_fit().

Details

Preparing Data for Nested Forecasting

Use extend_timeseries(), nest_timeseries(), and split_nested_timeseries() for preparing data for Nested Forecasting. The structure must be a nested data frame, which is suppplied in modeltime_nested_fit(nested_data).

Fitting Models

Models must be in the form of ⁠tidymodels workflow⁠ objects. The models can be provided in two ways:

1. Using ... (dots): The workflow objects can be provided as dots.

2. Using model_list parameter: You can supply one or more workflow objects that are wrapped in a list().

Controlling the fitting process

A control object can be provided during fitting to adjust the verbosity and parallel processing. See control_nested_fit().

modeltime documentation built on Oct. 23, 2024, 1:07 a.m.