forecast: Forecasting Functions for Time Series and Linear Models

Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.

Version: 6.2
Depends: R (≥ 3.0.2), stats, graphics, zoo, timeDate
Imports: tseries, fracdiff, Rcpp (≥ 0.11.0), nnet, colorspace, parallel
LinkingTo: Rcpp (≥ 0.11.0), RcppArmadillo (≥ 0.2.35)
Suggests: testthat, fpp
Published: 2015-10-20
Author: Rob J Hyndman. Contributors include George Athanasopoulos, Christoph Bergmeir, Carlos Cinelli, Yousaf Khan, Zach Mayer, Slava Razbash, Drew Schmidt, David Shaub, Yuan Tang, Earo Wang, Zhenyu Zhou.
Maintainer: Rob J Hyndman <Rob.Hyndman at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: forecast citation info
Materials: README ChangeLog
In views: Econometrics, Environmetrics, Finance, TimeSeries
CRAN checks: forecast results


Reference manual: forecast.pdf
Package source: forecast_6.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: forecast_6.1.tgz, r-oldrel: forecast_6.1.tgz
OS X Mavericks binaries: r-release: forecast_6.2.tgz
Old sources: forecast archive

Reverse dependencies:

Reverse depends: caschrono, demography, expsmooth, fma, forecTheta, fpp, ftsa, hts, ilc, MAPA, Mcomp, RcmdrPlugin.epack, Rssa, StMoMo, TSPred, ZRA
Reverse imports: bfast, lfl, marketeR, midasr, tsDyn, tsoutliers
Reverse suggests: dplR, gamclass, ggfortify, lifecontingencies, mFilter, portes, rainbow