forecast (6.2)

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.

Maintainer: Rob J Hyndman
Author(s): 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.

License: GPL (>= 2)

Uses: colorspace, fracdiff, nnet, Rcpp, timeDate, tseries, zoo, testthat, fpp
Reverse depends: bfast, caschrono, ChangeAnomalyDetection, demography, dendrometeR, Dowd, EnvCpt, expsmooth, fma, forecastHybrid, forecTheta, forega, fpp, fpp2, ftsa, hts, MAPA, Mcomp, nnfor, portes, RcmdrPlugin.epack, Rlgt, Rssa, spTimer, thief, Tushare, ZRA
Reverse suggests: AER, aurelius, caschrono, corset, dplR, epimdr, gamclass, ggfortify, lifecontingencies, mFilter, origami, pander, pmml, portes, rainbow, smooth, sophisthse, tactile, trajectories, tsbox, XLConnect
Reverse enhances: tsDyn

Released almost 4 years ago.