fable-package: fable: Forecasting Models for Tidy Time Series

In fable: Forecasting Models for Tidy Time Series

fable: Forecasting Models for Tidy Time Series

Description

Provides a collection of commonly used univariate and multivariate time series forecasting models including automatically selected exponential smoothing (ETS) and autoregressive integrated moving average (ARIMA) models. These models work within the 'fable' framework provided by the 'fabletools' package, which provides the tools to evaluate, visualise, and combine models in a workflow consistent with the tidyverse.

Author(s)

Maintainer: Mitchell O'Hara-Wild [e-mail]

Authors:

• Rob Hyndman

• Earo Wang

Other contributors:

• Gabriel Caceres (NNETAR implementation) [contributor]

• Christoph Bergmeir (ORCID) [contributor]

• Tim-Gunnar Hensel [contributor]

• Timothy Hyndman [contributor]

See Also

Useful links:

• https://fable.tidyverts.org

• https://github.com/tidyverts/fable

• Report bugs at https://github.com/tidyverts/fable/issues

fable documentation built on March 31, 2023, 8:13 p.m.