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'.

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
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

Documentation:

Reference manual: sweep.pdf
Vignettes: Introduction to sweep
Forecasting Time Series Groups in the tidyverse
Forecasting Using Multiple Models

Downloads:

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
Old sources: sweep archive

Reverse dependencies:

Reverse imports: anomalize

Linking:

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