Package: sweep 0.2.5.9000

Matt Dancho

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:Matt Dancho [aut, cre], Davis Vaughan [aut]

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

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

Peer review:

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

Datasets:
  • bike_sales - Fictional sales data for bike shops purchasing Cannondale bikes

On CRAN:

broomforecastforecasting-modelspredictiontidytidyversetimetime-seriestimeseries

10.78 score 155 stars 1 packages 375 scripts 26k downloads 6 exports 130 dependencies

Last updated 11 months agofrom:940f287164. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 25 2024
R-4.5-winNOTEOct 25 2024
R-4.5-linuxNOTEOct 25 2024
R-4.4-winOKOct 25 2024
R-4.4-macOKOct 25 2024
R-4.3-winOKOct 25 2024
R-4.3-macOKOct 25 2024

Exports:%>%sw_augmentsw_glancesw_sweepsw_tidysw_tidy_decomp

Dependencies:anytimeaskpassbackportsbase64encBHbitbit64broombslibcachemclassclicliprclockcodetoolscolorspacecpp11crayoncrosstalkcurldata.tablediagramdigestdplyrevaluatefansifarverfastmapfontawesomeforcatsforecastfracdifffsfurrrfuturefuture.applygenericsggplot2globalsgluegowergtablehardhathighrhmshtmltoolshtmlwidgetshttripredisobandjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelavalazyevallifecyclelistenvlmtestlubridatemagrittrMASSMatrixmemoisemgcvmimemunsellnlmennetnumDerivopensslpadrparallellypillarpkgconfigplotlyprettyunitsprodlimprogressprogressrpromisespurrrquadprogquantmodR6rappdirsRColorBrewerRcppRcppArmadilloRcppRollreadrrecipesrlangrmarkdownrpartrsamplesassscalesshapesliderSQUAREMstringistringrsurvivalsystibbletidyrtidyselecttimechangetimeDatetimetktinytextseriestsfeaturesTTRtzdburcautf8vctrsviridisLitevroomwarpwithrxfunxtsyamlzoo

Forecasting Time Series Groups in the tidyverse

Matt Dancho

Rendered fromSW01_Forecasting_Time_Series_Groups.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2023-12-08
Started: 2017-04-12

Forecasting Using Multiple Models

Matt Dancho

Rendered fromSW02_Forecasting_Multiple_Models.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2023-12-08
Started: 2017-04-13

Introduction to sweep

Matt Dancho

Rendered fromSW00_Introduction_to_sweep.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2023-12-08
Started: 2017-04-11

Readme and manuals

Help Manual

Help pageTopics
Adds a sequential index column to a data frameadd_index
Print the ARIMA model parametersarima_string
Print the BATS model parametersbats_string
Fictional sales data for bike shops purchasing Cannondale bikesbike_sales
Augment data according to a tidied modelsw_augment
Augments datasw_augment_columns
Default augment methodsw_augment.default
Construct a single row summary "glance" of a model, fit, or other objectsw_glance
Default glance methodsw_glance.default
Tidy forecast objectssw_sweep
Tidy the result of a time-series model into a summary tibblesw_tidy
Coerces decomposed time-series objects to tibble format.sw_tidy_decomp
Default tidying methodsw_tidy.default
Print the TBATS model parameterstbats_string
Tidying methods for ARIMA modeling of time seriessw_augment.Arima sw_glance.Arima sw_tidy.Arima sw_tidy.stlm tidiers_arima
Tidying methods for BATS and TBATS modeling of time seriessw_augment.bats sw_glance.bats sw_tidy.bats sw_tidy_decomp.bats tidiers_bats
Tidying methods for decomposed time seriessw_tidy_decomp.decomposed.ts tidiers_decomposed_ts
Tidying methods for ETS (Error, Trend, Seasonal) exponential smoothing modeling of time seriessw_augment.ets sw_glance.ets sw_tidy.ets sw_tidy_decomp.ets tidiers_ets
Tidying methods for HoltWinters modeling of time seriessw_augment.HoltWinters sw_glance.HoltWinters sw_tidy.HoltWinters sw_tidy_decomp.HoltWinters tidiers_HoltWinters
Tidying methods for Nural Network Time Series modelssw_augment.nnetar sw_glance.nnetar sw_tidy.nnetar tidiers_nnetar
Tidying methods for STL (Seasonal, Trend, Level) decomposition of time seriessw_augment.stlm sw_glance.stlm sw_tidy.stl sw_tidy_decomp.stl sw_tidy_decomp.stlm tidiers_stl
Tidying methods for StructTS (Error, Trend, Seasonal) / exponential smoothing modeling of time seriessw_augment.StructTS sw_glance.StructTS sw_tidy.StructTS tidiers_StructTS
Validates data frame has column named the same name as variable rename_indexvalidate_index