Contains functions, which facilitate downloading, loading and preparing data from 'M5 Forecasting' challenges (by 'University of Nicosia', hosted on 'Kaggle'). The data itself is set of time series of different product sales in 'Walmart'. The package also includes a ready-to-use built-in M5 subset named 'tiny_m5'. For detailed information about the challenges, see: Makridakis, S. & Spiliotis, E. & Assimakopoulos, V. (2020). <doi:10.1016/j.ijforecast.2021.10.009>.
Version: | 0.1.1 |
Depends: | R (≥ 3.5.0) |
Imports: | data.table, stringi, lubridate |
Suggests: | ggplot2, knitr, testthat (≥ 3.0.0), rmarkdown, zeallot |
Published: | 2022-09-12 |
DOI: | 10.32614/CRAN.package.m5 |
Author: | Krzysztof Joachimiak
|
Maintainer: | Krzysztof Joachimiak <joachimiak.krzysztof at gmail.com> |
BugReports: | https://github.com/krzjoa/m5/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/krzjoa/m5, https://krzjoa.github.io/m5/ |
NeedsCompilation: | no |
Materials: | README |
In views: | TimeSeries |
CRAN checks: | m5 results [issues need fixing before 2025-05-28] |
Reference manual: | m5.pdf |
Vignettes: |
demand_classification |
Package source: | m5_0.1.1.tar.gz |
Windows binaries: | r-devel: m5_0.1.1.zip, r-release: m5_0.1.1.zip, r-oldrel: m5_0.1.1.zip |
macOS binaries: | r-release (arm64): m5_0.1.1.tgz, r-oldrel (arm64): m5_0.1.1.tgz, r-release (x86_64): m5_0.1.1.tgz, r-oldrel (x86_64): m5_0.1.1.tgz |
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