Package: prophet
Title: Automatic Forecasting Procedure
Version: 1.1.7
Date: 2026-01-22
Authors@R: c(
  person("Cuong", "Duong", email = "cuong.duong242@gmail.com", role = c("cre", "aut")),
  person("Sean", "Taylor", email = "sjtz@pm.me", role = "aut"),
  person("Ben", "Letham", email = "bletham@fb.com", role = "aut")
  )
Description: 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.
URL: https://github.com/facebook/prophet
BugReports: https://github.com/facebook/prophet/issues
Depends: R (>= 3.4.0), Rcpp (>= 0.12.0), rlang (>= 0.3.0.1)
Imports: dplyr (>= 0.7.7), dygraphs (>= 1.1.1.4), extraDistr, ggplot2,
        grid, lubridate, methods, RcppParallel (>= 5.0.1), rstan (>=
        2.18.1), rstantools (>= 2.0.0), scales, StanHeaders, stats,
        tidyr (>= 0.6.1), xts
Suggests: cmdstanr, posterior, knitr, testthat, readr, rmarkdown
Additional_repositories: https://stan-dev.r-universe.dev
SystemRequirements: GNU make, C++17
Biarch: true
License: MIT + file LICENSE
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1),
        RcppEigen (>= 0.3.3.3.0), rstan (>= 2.18.1), StanHeaders (>=
        2.18.0)
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.2.0
NeedsCompilation: yes
Packaged: 2026-01-22 01:40:13 UTC; runner
Author: Cuong Duong [cre, aut],
  Sean Taylor [aut],
  Ben Letham [aut]
Maintainer: Cuong Duong <cuong.duong242@gmail.com>
Repository: CRAN
Date/Publication: 2026-01-22 08:20:02 UTC
Built: R 4.6.0; x86_64-w64-mingw32; 2026-03-10 04:59:39 UTC; windows
Archs: x64
