cat2cat: Mapping of a Categorical Variable in a Panel Dataset

There are offered automatic methods to map a categorical variable according to a specific encoding across different time points. The main rule is to replicate the observation if it could be assign to a few categories. Then using simple frequencies or statistical methods to approximate probabilities of being assign to each of them. This algorithm was invented and implemented in the paper by (Nasinski, Majchrowska and Broniatowska (2020) <doi:10.24425/cejeme.2020.134747>).

Version: 0.2.1
Depends: R (≥ 3.6)
Imports: rlang, caret, progress, randomForest, MASS, tidyr, dplyr, data.table, assertthat
Suggests: knitr, rmarkdown, pacman, testthat, magrittr, igraph
Published: 2021-03-27
Author: Maciej Nasinski [aut, cre]
Maintainer: Maciej Nasinski <nasinski.maciej at gmail.com>
BugReports: https://github.com/Polkas/cat2cat/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/Polkas/cat2cat
NeedsCompilation: no
Materials: NEWS
CRAN checks: cat2cat results

Documentation:

Reference manual: cat2cat.pdf
Vignettes: cat2cat - Introduction

Downloads:

Package source: cat2cat_0.2.1.tar.gz
Windows binaries: r-devel: cat2cat_0.2.1.zip, r-release: cat2cat_0.2.1.zip, r-oldrel: cat2cat_0.2.1.zip
macOS binaries: r-release (arm64): cat2cat_0.2.1.tgz, r-release (x86_64): cat2cat_0.2.1.tgz, r-oldrel: cat2cat_0.2.1.tgz
Old sources: cat2cat archive

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