conformalRegressorByHorizon

This function creates a conformal regressor that accounts for increasing
uncertainty at longer forecast horizons. It uses separate nonconformity
score distributions for each horizon h=1,2,3,..., resulting in prediction
intervals that naturally widen as the forecast horizon increases
(trumpet-shaped intervals).

Conformal time series forecasting using the caret infrastructure.
It provides access to state-of-the-art machine learning models for forecasting
applications. The hyperparameter of each model is selected based on time
series cross-validation, and forecasting is done recursively.

Resul Akay

caretForecast

Conformal Time Series Forecasting Using State of Art Machine
Learning Algorithms

conformalRegressorByHorizon function

<dl><dt>horizon_errors</dt>
<dd>A named list where each element contains sorted
absolute errors for that horizon. Names should be "h1", "h2", etc.
This is typically produced by <code>calibrate_horizon_scores()</code>.</dd></dl>

Arguments

Author

Fit a horizon-specific conformal regressor for time series forecasting. — conformalRegressorByHorizon

<dl>

<dt>horizon_errors</dt>
<dd>A named list where each element contains sorted
absolute errors for that horizon. Names should be "h1", "h2", etc.
This is typically produced by <code>calibrate_horizon_scores()</code>.</dd>

</dl>

conformalRegressorByHorizon: Fit a horizon-specific conformal regressor for time series forecasting.

Description

Usage

Value

Arguments

Author

References