Package: sweep 0.2.5.9000
![](https://github.com/business-science/sweep/raw/HEAD/man/figures/logo.png)
sweep:Tidy Tools for Forecasting
Tidies up the forecasting modeling and prediction work flow, extends the 'broom' package with 'sw_tidy', 'sw_glance', 'sw_augment', and 'sw_tidy_decomp' functions for various forecasting models, and enables converting 'forecast' objects to "tidy" data frames with 'sw_sweep'.
Authors:
sweep_0.2.5.9000.tar.gz
sweep_0.2.5.9000.zip(r-4.5)sweep_0.2.5.9000.zip(r-4.4)sweep_0.2.5.9000.zip(r-4.3)
sweep_0.2.5.9000.tgz(r-4.4-any)sweep_0.2.5.9000.tgz(r-4.3-any)
sweep_0.2.5.9000.tar.gz(r-4.5-noble)sweep_0.2.5.9000.tar.gz(r-4.4-noble)
sweep_0.2.5.9000.tgz(r-4.4-emscripten)sweep_0.2.5.9000.tgz(r-4.3-emscripten)
sweep.pdf |sweep.html✨
sweep/json (API)
NEWS
# Installsweep in R: |
install.packages('sweep',repos = c('https://business-science.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/business-science/sweep/issues
- bike_sales - Fictional sales data for bike shops purchasing Cannondale bikes
broomforecastforecasting-modelspredictiontidytidyversetimetime-seriestimeseries
Last updated 6 months agofrom:940f287164
Exports:%>%sw_augmentsw_glancesw_sweepsw_tidysw_tidy_decomp
Dependencies:anytimeaskpassbackportsbase64encBHbitbit64broombslibcachemclassclicliprclockcodetoolscolorspacecpp11crayoncrosstalkcurldata.tablediagramdigestdplyrellipsisevaluatefansifarverfastmapfontawesomeforcatsforecastfracdifffsfurrrfuturefuture.applygenericsggplot2globalsgluegowergtablehardhathighrhmshtmltoolshtmlwidgetshttripredisobandjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelavalazyevallifecyclelistenvlmtestlubridatemagrittrMASSMatrixmemoisemgcvmimemunsellnlmennetnumDerivopensslpadrparallellypillarpkgconfigplotlyprettyunitsprodlimprogressprogressrpromisespurrrquadprogquantmodR6rappdirsRColorBrewerRcppRcppArmadilloRcppRollreadrrecipesrlangrmarkdownrpartrsamplesassscalesshapesliderSQUAREMstringistringrsurvivalsystibbletidyrtidyselecttimechangetimeDatetimetktinytextseriestsfeaturesTTRtzdburcautf8vctrsviridisLitevroomwarpwithrxfunxtsyamlzoo
Forecasting Time Series Groups in the tidyverse
Rendered fromSW01_Forecasting_Time_Series_Groups.Rmd
usingknitr::rmarkdown
on Jun 27 2024.Last update: 2023-12-08
Started: 2017-04-12
Forecasting Using Multiple Models
Rendered fromSW02_Forecasting_Multiple_Models.Rmd
usingknitr::rmarkdown
on Jun 27 2024.Last update: 2023-12-08
Started: 2017-04-13
Introduction to sweep
Rendered fromSW00_Introduction_to_sweep.Rmd
usingknitr::rmarkdown
on Jun 27 2024.Last update: 2023-12-08
Started: 2017-04-11