fable: Forecasting Models for Tidy Time Series

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.

Package details

AuthorMitchell O'Hara-Wild [aut, cre], Rob Hyndman [aut], Earo Wang [aut], Gabriel Caceres [ctb] (NNETAR implementation), Christoph Bergmeir [ctb] (<https://orcid.org/0000-0002-3665-9021>), Tim-Gunnar Hensel [ctb], Timothy Hyndman [ctb]
MaintainerMitchell O'Hara-Wild <mail@mitchelloharawild.com>
URL https://fable.tidyverts.org https://github.com/tidyverts/fable
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the fable package in your browser

Any scripts or data that you put into this service are public.

fable documentation built on May 29, 2024, 7:25 a.m.