tidyverts/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.

Getting started

Package details

Maintainer
LicenseGPL-3
Version0.4.1.9000
URL https://fable.tidyverts.org https://github.com/tidyverts/fable
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("tidyverts/fable")
tidyverts/fable documentation built on Nov. 30, 2024, 10:49 p.m.