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: 5.6
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: 2014-09-24
Author: Rob J Hyndman with contributions from George Athanasopoulos, Slava Razbash, Drew Schmidt, Zhenyu Zhou, Yousaf Khan, Christoph Bergmeir, Earo Wang
Maintainer: Rob J Hyndman <Rob.Hyndman at monash.edu>
BugReports: https://github.com/robjhyndman/forecast/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://robjhyndman.com/software/forecast/
NeedsCompilation: yes
Materials: README ChangeLog
In views: Econometrics, Environmetrics, Finance, TimeSeries
CRAN checks: forecast results

Downloads:

Reference manual: forecast.pdf
Package source: forecast_5.6.tar.gz
Windows binaries: r-devel: forecast_5.6.zip, r-release: forecast_5.6.zip, r-oldrel: forecast_5.6.zip
OS X Snow Leopard binaries: r-release: forecast_5.6.tgz, r-oldrel: forecast_5.6.tgz
OS X Mavericks binaries: r-release: forecast_5.6.tgz
Old sources: forecast archive

Reverse dependencies:

Reverse depends: caschrono, demography, expsmooth, fma, fpp, ftsa, hts, MAPA, Mcomp, RcmdrPlugin.epack, Rssa, spTimer
Reverse imports: bfast, tsDyn, tsoutliers
Reverse suggests: dplR, gamclass, lifecontingencies, mFilter, portes, XLConnect