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:
modeltime.ensemble_1.0.4.tar.gz
modeltime.ensemble_1.0.4.zip(r-4.5)modeltime.ensemble_1.0.4.zip(r-4.4)modeltime.ensemble_1.0.4.zip(r-4.3)
modeltime.ensemble_1.0.4.tgz(r-4.4-any)modeltime.ensemble_1.0.4.tgz(r-4.3-any)
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://business-science.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/business-science/modeltime.ensemble/issues
ensembleensemble-learningforecastforecastingmodeltimestackingstacking-ensembletidymodelstimetime-seriestimeseries
Last updated 4 months agofrom:37f80be857. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 18 2024 |
| R-4.5-win | OK | Oct 18 2024 |
| R-4.5-linux | OK | Oct 18 2024 |
| R-4.4-win | OK | Oct 18 2024 |
| R-4.4-mac | OK | Oct 18 2024 |
| R-4.3-win | OK | Oct 18 2024 |
| R-4.3-mac | OK | Oct 18 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 Oct 18 2024.Last update: 2023-12-13
Started: 2021-04-03
Getting Started with Modeltime Ensemble
Rendered fromgetting-started-with-modeltime-ensemble.Rmdusingknitr::rmarkdownon Oct 18 2024.Last update: 2023-12-13
Started: 2020-09-21
Iterative Forecasting with Nested Ensembles
Rendered fromnested-ensembles.Rmdusingknitr::rmarkdownon Oct 18 2024.Last update: 2023-12-13
Started: 2021-10-13
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Creates an Ensemble Model using Mean/Median Averaging | ensemble_average |
| Creates a Stacked Ensemble Model from a Model Spec | ensemble_model_spec |
| Nested Ensemble Average | ensemble_nested_average |
| Nested Ensemble Weighted | ensemble_nested_weighted |
| Creates a Weighted Ensemble Model | ensemble_weighted |
