Package: modeltime.ensemble 1.0.4

Matt Dancho

modeltime.ensemble: Ensemble Algorithms for Time Series Forecasting with Modeltime

A 'modeltime' extension that implements time series ensemble forecasting methods including model averaging, weighted averaging, and stacking. These techniques are popular methods to improve forecast accuracy and stability.

Authors:Matt Dancho [aut, cre], Business Science [cph]

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modeltime.ensemble.pdf |modeltime.ensemble.html✨
modeltime.ensemble/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/business-science/modeltime.ensemble/issues

Pkgdown site:https://business-science.github.io

On CRAN:

ensembleensemble-learningforecastforecastingmodeltimestackingstacking-ensembletidymodelstimetime-seriestimeseries

8.29 score 75 stars 143 scripts 436 downloads 15 exports 191 dependencies

Last updated 6 months agofrom:37f80be857. Checks:7 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 16 2025
R-4.5-winOKJan 16 2025
R-4.5-linuxOKJan 16 2025
R-4.4-winOKJan 16 2025
R-4.4-macOKJan 16 2025
R-4.3-winOKJan 16 2025
R-4.3-macOKJan 16 2025

Exports::=.data%>%as_labelas_nameenquoenquosensemble_averageensemble_model_specensemble_nested_averageensemble_nested_weightedensemble_weightedexprsymsyms

Dependencies:abindanytimeaskpassbackportsbase64encBHbigDbitbit64bitopsbroombslibcachemcallrcheckmateclassclicliprclockcodetoolscolorspacecommonmarkconflictedcpp11crayoncrosstalkcurldata.tabledescdiagramdialsDiceDesigndigestdistributionaldoFuturedoParalleldplyrdygraphsevaluateextraDistrfansifarverfastmapfontawesomeforcatsforeachforecastfracdifffsfurrrfuturefuture.applygenericsggplot2glmnetglobalsgluegowerGPfitgridExtragtgtablehardhathighrhmshtmltoolshtmlwidgetshttrinferinlineipredisobanditeratorsjanitorjquerylibjsonlitejuicyjuiceKernSmoothknitrlabelinglaterlatticelavalazyevallhslifecyclelistenvlmtestloolubridatemagrittrmarkdownMASSMatrixmatrixStatsmemoisemgcvmimemodeldatamodelenvmodeltimemodeltime.resamplemunsellnlmennetnumDerivopensslpadrparallellyparsnippatchworkpillarpkgbuildpkgconfigplotlyposteriorprettyunitsprocessxprodlimprogressprogressrpromisesprophetpspurrrquadprogquantmodQuickJSRR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRcppRollreactablereactRreadrrecipesrlangrmarkdownrpartrsamplerstanrstantoolsrstudioapisassscalessfdshapeslidersnakecaseSQUAREMStanHeadersstringistringrsurvivalsystensorAtibbletictoctidymodelstidyrtidyselecttimechangetimeDatetimetktinytextseriestsfeaturesTTRtunetzdburcautf8V8vctrsviridisLitevroomwarpwithrworkflowsworkflowsetsxfunxgboostxml2xtsyamlyardstickzoo

Autoregressive Forecasting (Recursive Ensembles)

Rendered fromrecursive-ensembles.Rmdusingknitr::rmarkdownon Jan 16 2025.

Last update: 2023-12-13
Started: 2021-04-03

Getting Started with Modeltime Ensemble

Rendered fromgetting-started-with-modeltime-ensemble.Rmdusingknitr::rmarkdownon Jan 16 2025.

Last update: 2023-12-13
Started: 2020-09-21

Iterative Forecasting with Nested Ensembles

Rendered fromnested-ensembles.Rmdusingknitr::rmarkdownon Jan 16 2025.

Last update: 2023-12-13
Started: 2021-10-13