Automatic Forecasting Procedure

Implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.


Reference manual

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0.5 by Sean Taylor, 4 months ago

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Authors: Sean Taylor [cre, aut] , Ben Letham [aut]

Documentation:   PDF Manual  

Task views: Time Series Analysis, Missing Data

BSD_3_clause + file LICENSE license

Imports dplyr, dygraphs, extraDistr, ggplot2, grid, rstan, scales, stats, tidyr, xts

Depends on Rcpp, rlang

Suggests knitr, testthat, readr

System requirements: C++11

Imported by promotionImpact.

See at CRAN