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: 0.2.3
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
Suggests: forcats, knitr, rmarkdown, testthat, purrr, readr, robets, stringr, scales, tidyquant, tidyverse, fracdiff
Published: 2020-07-10
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_0.2.3.tar.gz
Windows binaries: r-devel: sweep_0.2.3.zip, r-release: sweep_0.2.3.zip, r-oldrel: sweep_0.2.3.zip
macOS binaries: r-release: sweep_0.2.3.tgz, r-oldrel: sweep_0.2.3.tgz
Old sources: sweep archive

Reverse dependencies:

Reverse imports: anomalize


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