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]

modeltime.ensemble_1.0.4.tar.gz
modeltime.ensemble_1.0.4.tar.gz(r-4.5-noble)modeltime.ensemble_1.0.4.tar.gz(r-4.4-noble)
modeltime.ensemble_1.0.4.tgz(r-4.4-emscripten)modeltime.ensemble_1.0.4.tgz(r-4.3-emscripten)
modeltime.ensemble.pdf |modeltime.ensemble.html
modeltime.ensemble/json (API)
NEWS

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

Peer review:

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

15 exports 1 stars 0.23 score 191 dependencies 126 scripts 797 downloads

Last updated 2 months agofrom:d97c425729. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKAug 19 2024
R-4.5-linuxOKAug 19 2024

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 Aug 19 2024.

Last update: 2024-07-20
Started: 2021-04-05

Getting Started with Modeltime Ensemble

Rendered fromgetting-started-with-modeltime-ensemble.Rmdusingknitr::rmarkdownon Aug 19 2024.

Last update: 2024-07-20
Started: 2020-10-07

Iterative Forecasting with Nested Ensembles

Rendered fromnested-ensembles.Rmdusingknitr::rmarkdownon Aug 19 2024.

Last update: 2024-07-20
Started: 2021-10-19