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'.
Version: | 0.2.5 |
Depends: | R (≥ 3.3.0) |
Imports: | broom (≥ 0.5.6), dplyr (≥ 1.0.0), forecast (≥ 8.0), lubridate (≥ 1.6.0), tibble (≥ 1.2), tidyr (≥ 1.0.0), timetk (≥ 2.1.0), rlang, tidyverse, tidyquant |
Suggests: | forcats, knitr, rmarkdown, testthat, purrr, readr, stringr, scales, fracdiff |
Published: | 2023-07-06 |
DOI: | 10.32614/CRAN.package.sweep |
Author: | Matt Dancho [aut, cre], Davis Vaughan [aut] |
Maintainer: | Matt Dancho <mdancho at business-science.io> |
BugReports: | https://github.com/business-science/sweep/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/business-science/sweep |
NeedsCompilation: | no |
Materials: | README NEWS |
In views: | TimeSeries |
CRAN checks: | sweep results |
Reference manual: | sweep.pdf |
Vignettes: |
Introduction to sweep Forecasting Time Series Groups in the tidyverse Forecasting Using Multiple Models |
Package source: | sweep_0.2.5.tar.gz |
Windows binaries: | r-devel: sweep_0.2.5.zip, r-release: sweep_0.2.5.zip, r-oldrel: sweep_0.2.5.zip |
macOS binaries: | r-release (arm64): sweep_0.2.5.tgz, r-oldrel (arm64): sweep_0.2.5.tgz, r-release (x86_64): sweep_0.2.5.tgz, r-oldrel (x86_64): sweep_0.2.5.tgz |
Old sources: | sweep archive |
Reverse imports: | anomalize |
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