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forecast
Forecasting Functions for Time Series and Linear Models
View on CRAN: Click
here
Download and install forecast package within the R console
Install from CRAN:
install.packages("forecast")
Install from Github:
library("remotes")
install_github("cran/forecast") Install by package version:
library("remotes")
install_version("forecast", "8.23.0") Attach the package and use:
library("forecast")
Maintained by
Rob Hyndman
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.forecast . https://github.com/robjhyndman/forecast/issues . https://pkg.robjhyndman.com/forecast/ . https://github.com/robjhyndman/forecast . forecast citation info . forecast results . forecast.pdf . Automatic Time Series Forecasting: the forecast Package for R (Hyndman & Khandakar, JSS 2008) . forecast_8.23.0.tar.gz . forecast_8.23.0.zip . forecast_8.23.0.zip . forecast_8.23.0.zip . forecast_8.23.0.tgz . forecast_8.23.0.tgz . forecast_8.23.0.tgz . forecast_8.23.0.tgz . forecast_8.23.0.tgz . forecast_8.23.0.tgz . forecast archive . forecastHybrid . ATAforecasting . bayesforecast . forecasteR . forecastLSW . https://CRAN.R-project.org/package=forecast .
First Published: 2009-09-07
Latest Update: 2024-03-04
Description:
Methods and tools for displaying and analysing
univariate time series forecasts including exponential smoothing
via state space models and automatic ARIMA modelling.
How to cite:
Rob Hyndman (2009). forecast: Forecasting Functions for Time Series and Linear Models. R package version 8.23.0, https://cran.r-project.org/web/packages/forecast. Accessed 07 Apr. 2025.
Previous versions and publish date:
2.00 (2009-09-07 11:38), 2.01 (2009-09-18 22:24), 2.02 (2009-12-23 09:18), 2.03 (2009-12-24 11:42), 2.04 (2010-04-16 18:04), 2.05 (2010-05-11 07:33), 2.06 (2010-07-29 11:13), 2.07 (2010-09-09 14:08), 2.08 (2010-09-22 16:59), 2.09 (2010-10-15 12:06), 2.11 (2010-11-04 08:15), 2.12 (2011-01-19 09:21), 2.13 (2011-02-16 12:36), 2.14 (2011-03-04 15:49), 2.15 (2011-03-05 17:40), 2.16 (2011-03-07 06:40), 2.17 (2011-04-06 12:12), 2.19 (2011-06-04 10:07), 3.00 (2011-08-24 11:30), 3.02 (2011-08-25 14:28), 3.03 (2011-09-02 14:39), 3.04 (2011-09-23 13:45), 3.05 (2011-10-03 07:40), 3.06 (2011-10-04 09:25), 3.07 (2011-10-11 17:24), 3.08 (2011-10-15 21:53), 3.09 (2011-10-18 08:00), 3.10 (2011-10-27 07:46), 3.11 (2011-11-02 18:25), 3.12 (2011-11-16 13:16), 3.13 (2011-11-20 11:24), 3.14 (2011-12-09 10:16), 3.15 (2011-12-22 14:37), 3.16 (2011-12-24 13:10), 3.17 (2012-02-02 17:33), 3.18 (2012-02-17 08:38), 3.19 (2012-02-22 09:25), 3.20 (2012-04-02 08:49), 3.21 (2012-04-30 07:37), 3.22 (2012-06-07 08:05), 3.23 (2012-07-18 11:41), 3.24 (2012-07-23 07:26), 3.25 (2012-09-11 19:01), 4.00 (2012-11-27 07:56), 4.01 (2013-01-22 08:23), 4.02 (2013-03-06 07:17), 4.03 (2013-03-17 12:28), 4.04 (2013-04-22 16:55), 4.05 (2013-06-19 08:53), 4.06 (2013-06-30 10:14), 4.7 (2013-09-27 07:55), 4.8 (2013-09-30 08:07), 5.0 (2014-01-17 06:13), 5.1 (2014-02-08 08:09), 5.2 (2014-02-24 08:05), 5.3 (2014-03-24 13:26), 5.4 (2014-05-08 07:19), 5.5 (2014-08-12 06:52), 5.6 (2014-09-24 06:54), 5.7 (2014-12-17 07:21), 5.8 (2015-01-06 17:30), 5.9 (2015-02-26 16:46), 6.0 (2015-05-09 23:14), 6.1 (2015-05-12 12:37), 6.2 (2015-10-20 08:06), 7.0 (2016-04-04 01:21), 7.1 (2016-04-14 14:53), 7.2 (2016-09-09 10:13), 7.3 (2016-10-13 00:38), 8.0 (2017-02-23 08:31), 8.1 (2017-06-18 01:07), 8.2 (2017-09-25 20:12), 8.3 (2018-04-11 17:19), 8.4 (2018-06-21 15:59), 8.5 (2019-01-18 11:50), 8.6 (2019-04-16 15:32), 8.7 (2019-04-29 07:40), 8.8 (2019-08-02 17:10), 8.9 (2019-08-22 13:50), 8.10 (2019-12-05 13:10), 8.11 (2020-02-09 13:20), 8.12 (2020-03-31 16:10), 8.13 (2020-09-12 08:00), 8.14 (2021-03-11 09:10), 8.15 (2021-06-01 13:20), 8.16 (2022-01-10 05:32), 8.17.0 (2022-07-25 16:10), 8.18 (2022-10-02 05:10), 8.19 (2022-11-21 00:10), 8.20 (2023-01-06 15:50), 8.21.1 (2023-08-31 17:10), 8.21 (2023-02-27 23:02), 8.22.0 (2024-03-04 07:10)
Other packages that cited forecast R package
View forecast citation profile
Other R packages that forecast depends,
imports, suggests or enhances
Complete documentation for forecast
Functions, R codes and Examples using
the forecast R package
Some associated functions: Acf . Arima . BoxCox.lambda . BoxCox . CV . CVar . accuracy.default . arfima . arima.errors . arimaorder . auto.arima . autolayer . autoplot.acf . autoplot.seas . autoplot.ts . baggedModel . bats . bizdays . bld.mbb.bootstrap . checkresiduals . croston . dm.test . dshw . easter . ets . findfrequency . fitted.Arima . forecast-package . forecast.Arima . forecast.HoltWinters . forecast.StructTS . forecast.baggedModel . forecast.bats . forecast.ets . forecast.lm . forecast.mlm . forecast.modelAR . forecast.mts . forecast.nnetar . forecast.stl . forecast.ts . fourier . gas . geom_forecast . getResponse . gghistogram . gglagplot . ggmonthplot . gold . is.constant . is.ets . is.forecast . ma . meanf . modelAR . monthdays . mstl . msts . na.interp . naive . ndiffs . nnetar . nsdiffs . ocsb.test . plot.Arima . plot.bats . plot.ets . plot.forecast . plot.mforecast . reexports . residuals.forecast . seasadj . seasonal . seasonaldummy . seasonplot . ses . simulate.ets . sindexf . splinef . subset.ts . taylor . tbats.components . tbats . thetaf . tsCV . tsclean . tsdisplay . tslm . tsoutliers . wineind . woolyrnq .
Some associated R codes: DM2.R . HoltWintersNew.R . acf.R . adjustSeasonalSeeds.R . arfima.R . arima.R . armaroots.R . attach.R . baggedModel.R . bats.R . bootstrap.R . calendar.R . checkAdmissibility.R . checkresiduals.R . clean.R . components.R . data.R . errors.R . ets.R . etsforecast.R . findfrequency.R . fitBATS.R . fitTBATS.R . forecast-package.R . forecast.R . forecast.varest.R . forecast2.R . forecastBATS.R . forecastTBATS.R . getResponse.R . ggplot.R . graph.R . guerrero.R . lm.R . makeMatrices.R . makeParamVector.R . mforecast.R . modelAR.R . mstl.R . msts.R . naive.R . newarima2.R . nnetar.R . residuals.R . seasadj.R . season.R . simulate.R . simulate_tbats.R . spline.R . subset.R . tbats.R . theta.R . tscv.R . unitRoot.R . whichmodels.R . wrangle.R . Full forecast package functions and examples
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