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

Maintainer: Rob Hyndman <Rob.Hyndman at monash.edu>

Author(s): Rob Hyndman*, Mitchell O'Hara-Wild*, Christoph Bergmeir*, Slava Razbash*, Earo Wang*

Install package and any missing dependencies by running this line in your R console:

install.packages("forecast")

Depends R (>= 3.0.2),
Imports stats, graphics, tseries, fracdiff, Rcpp(>=0.11.0), nnet, colorspace, parallel, ggplot2(>=2.0.0), magrittr, lmtest, zoo, timeDate
Suggests testthat, knitr, rmarkdown, expsmooth, rticles
Enhances
Linking to Rcpp(>=0.11.0), RcppArmadillo(>=0.2.35)

Package forecast
Materials
URL http://github.com/robjhyndman/forecast
Task Views Econometrics , Environmetrics , Finance , TimeSeries
Version 8.0
Published 2017-02-23
License GPL (>= 2)
BugReports https://github.com/robjhyndman/forecast/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks forecast check results
Package source forecast_8.0.tar.gz