cat2cat: Unify 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: |
0.3.3 |
| Depends: |
R (≥ 3.6) |
| Imports: |
MASS, assertthat |
| Suggests: |
caret, randomForest, knitr, rmarkdown, pacman, testthat, magrittr, dplyr |
| Published: |
2022-03-11 |
| 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,
https://polkas.github.io/cat2cat/ |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
cat2cat results |
Documentation:
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