robjhyndman/forecast

Health v2 · maintenance only

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1174 stars · 337 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

The R package forecast provides methods and tools for displaying and analysing univariate time series forecasts, including exponential smoothing via state space models and automatic ARIMA modelling. It is a mature, widely used CRAN package maintained by Rob Hyndman, with a tidyverse-oriented successor called fable.

Use cases

• forecast future values of a time series in R
• automatically fit an ARIMA model to time series data
• exponential smoothing forecasts with ETS state space models
• decompose a seasonal time series with STL and forecast it
• forecast high-frequency or complex seasonal data with TBATS
• plot time series forecasts with ggplot2 autoplot
• estimate prediction intervals for time series forecasts

When to choose

• you work in R and need classical statistical time series forecasting models like ARIMA, ETS, STL, or TBATS
• you want automatic model selection for univariate forecasting
• you need a battle-tested, well-documented package backed by an authoritative forecasting textbook
• you are following Hyndman's fpp2/fpp3 forecasting textbook examples

When to avoid

• you prefer a tidyverse-style workflow - consider the fable package instead
• you need deep learning or neural network based forecasting
• you work primarily in Python rather than R
• you need multivariate or cross-sectional hierarchical forecasting beyond this package's scope

Facets

library · maturity stable

data-science math data-visualization data-science time-series analytics cross-platform forecasting time-series arima ets exponential-smoothing stl tbats cran statistics r

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