Mapping of a Categorical Variable in a Panel Dataset
person("Maciej", "Nasinski", email = "nasinski.maciej@gmail.com", role = c("aut", "cre"))
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>).
methods, rlang, caret, progress, magrittr, randomForest, MASS,
tidyr, dplyr, data.table

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>).
rlang, caret, progress, randomForest, MASS, tidyr, dplyr,
data.table, assertthat
knitr, rmarkdown, pacman, testthat, magrittr

knitr, rmarkdown, pacman, testthat, magrittr, igraph

Unify a Categorical Variable in a Panel Dataset
rlang, progress, MASS, tidyr, dplyr, assertthat
caret, randomForest, knitr, rmarkdown, pacman, testthat,
magrittr, igraph

caret, randomForest, knitr, rmarkdown, pacman, testthat,
magrittr, dplyr

Handling an Inconsistent Coded Categorical Variable in a Panel
Dataset
There are offered automatic methods to map a categorical variable according to a specific mappings 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>).