Package: fable 0.4.1

Mitchell OHara-Wild

fable: Forecasting Models for Tidy Time Series

Provides a collection of commonly used univariate and multivariate time series forecasting models including automatically selected exponential smoothing (ETS) and autoregressive integrated moving average (ARIMA) models. These models work within the 'fable' framework provided by the 'fabletools' package, which provides the tools to evaluate, visualise, and combine models in a workflow consistent with the tidyverse.

Authors:Mitchell O'Hara-Wild [aut, cre], Rob Hyndman [aut], Earo Wang [aut], Gabriel Caceres [ctb], Christoph Bergmeir [ctb], Tim-Gunnar Hensel [ctb], Timothy Hyndman [ctb]

fable_0.4.1.tar.gz
fable_0.4.1.tar.gz(r-4.5-noble)fable_0.4.1.tar.gz(r-4.4-noble)
fable_0.4.1.tgz(r-4.4-emscripten)fable_0.4.1.tgz(r-4.3-emscripten)
fable.pdf |fable.html
fable/json (API)
NEWS

# Install 'fable' in R:
install.packages('fable', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tidyverts/fable/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

8.22 score 1 stars 6 packages 1.8k scripts 17k downloads 1 mentions 18 exports 50 dependencies

Last updated 20 days agofrom:2d398cf420. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-linux-x86_64OKNov 06 2024

Exports:%>%ARARIMAas_tsibblebreusch_godfreyCROSTONETSMEANNAIVENNETARRWSNAIVETHETATSLMunitroot_optionsVARVARIMAVECM

Dependencies:anytimeBHclicolorspacecpp11digestdistributionaldplyrellipsisfabletoolsfansifarvergenericsggdistggplot2gluegtableisobandlabelinglatticelifecyclelubridatemagrittrMASSMatrixmgcvmunsellnlmenumDerivpillarpkgconfigprogressrpurrrquadprogR6RColorBrewerRcpprlangscalesstringistringrtibbletidyrtidyselecttimechangetsibbleutf8vctrsviridisLitewithr

Forecasting with transformations

Rendered fromtransformations.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2021-02-03
Started: 2019-09-23

Introduction to fable

Rendered fromfable.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2021-05-16
Started: 2019-09-23

Readme and manuals

Help Manual

Help pageTopics
Estimate a AR modelAR report.AR
Estimate an ARIMA modelARIMA report.ARIMA
Breusch-Godfrey Testbreusch_godfrey breusch_godfrey.TSLM
Extract estimated states from an ETS model.components.ETS
Croston's methodCROSTON
Exponential smoothing state space modelETS report.ETS
Extract fitted values from a fable modelfitted.AR
Extract fitted values from a fable modelfitted.ARIMA
Extract fitted values from a fable modelfitted.croston
Extract fitted values from a fable modelfitted.ETS
Extract fitted values from a fable modelfitted.fable_theta
Extract fitted values from a fable modelfitted.model_mean
Extract fitted values from a fable modelfitted.NNETAR
Extract fitted values from a fable modelfitted.RW
Extract fitted values from a fable modelfitted.TSLM
Extract fitted values from a fable modelfitted.VAR
Forecast a model from the fable packageforecast.AR
Forecast a model from the fable packageforecast.ARIMA
Forecast a model from the fable packageforecast.croston
Forecast a model from the fable packageforecast.ETS
Forecast a model from the fable packageforecast.fable_theta
Forecast a model from the fable packageforecast.model_mean
Forecast a model from the fable packageforecast.NNETAR
Forecast a model from the fable packageforecast.RW
Forecast a model from the fable packageforecast.TSLM
Forecast a model from the fable packageforecast.VAR
Generate new data from a fable modelgenerate.AR
Generate new data from a fable modelgenerate.ARIMA
Generate new data from a fable modelgenerate.ETS
Generate new data from a fable modelgenerate.model_mean
Generate new data from a fable modelgenerate.NNETAR
Generate new data from a fable modelgenerate.RW
Generate new data from a fable modelgenerate.TSLM
Generate new data from a fable modelgenerate.VAR
Generate new data from a fable modelgenerate.VECM
Glance a ARglance.AR
Glance an ARIMA modelglance.ARIMA
Glance an ETS modelglance.ETS
Glance a theta methodglance.fable_theta
Glance a average method modelglance.model_mean
Glance a NNETAR modelglance.NNETAR
Glance a lag walk modelglance.RW
Glance a TSLMglance.TSLM
Glance a VARglance.VAR
Glance a VECMglance.VECM
Interpolate missing values from a fable modelinterpolate.ARIMA
Interpolate missing values from a fable modelinterpolate.model_mean
Interpolate missing values from a fable modelinterpolate.TSLM
Calculate impulse responses from a fable modelIRF.ARIMA
Calculate impulse responses from a fable modelIRF.VAR
Calculate impulse responses from a fable modelIRF.VECM
Mean modelsMEAN report.model_mean
Neural Network Time Series ForecastsNNETAR report.NNETAR
Refit an AR modelrefit.AR
Refit an ARIMA modelrefit.ARIMA
Refit an ETS modelrefit.ETS
Refit a MEAN modelrefit.model_mean
Refit a NNETAR modelrefit.NNETAR
Refit a lag walk modelrefit.RW
Refit a 'TSLM'refit.TSLM
Extract residuals from a fable modelresiduals.AR
Extract residuals from a fable modelresiduals.ARIMA
Extract residuals from a fable modelresiduals.croston
Extract residuals from a fable modelresiduals.ETS
Extract residuals from a fable modelresiduals.fable_theta
Extract residuals from a fable modelresiduals.model_mean
Extract residuals from a fable modelresiduals.NNETAR
Extract residuals from a fable modelresiduals.RW
Extract residuals from a fable modelresiduals.TSLM
Extract residuals from a fable modelresiduals.VAR
Random walk modelsNAIVE report.RW RW SNAIVE
Theta methodTHETA
Tidy a fable modeltidy.AR
Tidy a fable modeltidy.ARIMA
Tidy a fable modeltidy.croston
Tidy a fable modeltidy.ETS
Tidy a fable modeltidy.fable_theta
Tidy a fable modeltidy.model_mean
Tidy a fable modeltidy.NNETAR
Tidy a fable modeltidy.RW
Tidy a fable modeltidy.TSLM
Tidy a fable modeltidy.VAR
Fit a linear model with time series componentsreport.TSLM TSLM
Options for the unit root tests for order of integrationunitroot_options
Estimate a VAR modelreport.VAR VAR
Estimate a VARIMA modelfitted.VARIMA forecast.VARIMA generate.VARIMA glance.VARIMA IRF.VARIMA report.VARIMA residuals.VARIMA tidy.VARIMA VARIMA
Estimate a VECM modelVECM