NEWS

---

cat2cat 0.4.7 (2024-01-22)

• New cat2cat_ml_run function to check the ml models performance before cat2cat with ml option is run. Now, the ml models are more transparent.
• Add tests for cat2cat related journal (softwarex) paper.
• Add CITATION file.
• Internal changes to make the code base more clear.
• Replace itemize with describe in the latex documentation.

cat2cat 0.4.6 (2023-02-01)

• Add some ropensci standards, like CONTRIBUTING file and testthat version 3.
• Add LICENSE file.
• Update DESCRIPTION file.
• Update outdated URLs.
• cat2cat_agg has updated cat_var argument to two new ones, cat_var_old and cat_var_new.
• Rename the master to main branch.
• Improve tests and lintr related issues.

cat2cat 0.4.5 (2022-09-25)

• The freqs_df argument in the cat2cat function is moved from data to mappings part, it is backward compatible. Now it is consistent with the python cat2cat implementation.
• pkgcheck related fixes, like 80 chars per line.
• Improve data and library calls style.

cat2cat 0.4.4 (2022-08-31)

• Fix example in the cat2cat function.
• Improve documentation.
• Improve validation.

cat2cat 0.4.3

• Fix dummy_c2c to be backward compatible.
• Add more tests for base utils functions.
• Improve cat_apply_freq function performance.
• Improve documentation.
• Improve validation.

cat2cat 0.4.2 (2022-08-05)

• The ml argument in the dummy_c2c function is redefined, shorter names for a simpler usage.
• The cat2cat ml part is using direct cat_var for target (for an update) dataset now, not the one from the ml argument list.
• Improve procedure graphs.

cat2cat 0.4.1 (2022-06-08)

• additional cat2cat validation, if the trans table covers all needed levels.
• documentation and tests improvements.

cat2cat 0.4.0

• new syntax of the ml and data argument in the cat2cat::cat2cat function, two additional arguments each.
• prune_c2c scales the weights now, so still sum to one for each subject.
• new function dummy_c2c to add a default cat2cat columns to a data.frame.
• occupand occup_small datasets have 4 periods now.
• add the 4 periods example to the vignette.
• custom pkgdown reference.

cat2cat 0.3.3 (2022-03-11)

• improve the pkgdown website.
• deparse instead of deparse1.

cat2cat 0.3.2

• tinyverse world, even less dependencies.

cat2cat 0.3.1 (2022-02-06)

• updated README file.
• improved covr and tests.
• updated vignette.

cat2cat 0.3.0

• fixed the cat2cat function, the ml part is assuming that categorical variable is always named "code".
• fixed problems when using only one feature in the ml part of cat2cat function.
• persist NA values in a categorical variable in the cat2cat function.
• updated vignette.
• improved roxygen2 docs.
• transferred caret and randomForest packages to Suggests, they are delayed loaded now.
• styler of the code.
• more readable code.
• removed data.table from Imports.

cat2cat 0.2.1 (2021-03-27)

• usage of summary_c2c with the default df_new argument.
• plot_c2c roxygen2

cat2cat 0.2.0 (2020-12-08)

• plot_c2c

cat2cat 0.1.9

• vignette improvements

cat2cat 0.1.8

• pt inside summary_c2c
• VignetteIndexEntry

cat2cat 0.1.7 (2020-11-29)

• URL for doi in vignettes

cat2cat 0.1.6

• basic vignette
• rm .internal.selfref attr for mapped df
• assertthat instead of stopifnot

cat2cat 0.1.5

• data.R adding set.seed
• lack of a one bracket in description file

cat2cat 0.1.4

• remove the unnecessary imports in the DESCRIPTION file

cat2cat 0.1.3 (2020-09-22)

• Title reduce to less than 65 characters.
• doi of journal paper added to a description section in the DESCRIPTION file.
• unnecessary dontrun in data.R were removed.

cat2cat 0.1.2

• occup_small dataset to pass checks in terms of computation time of examples.
• data.table rbindlist.
• optimize for loop for ml models.

cat2cat 0.1.1

• Title format in Description file.
• spelling.

cat2cat 0.1.0

• More ml methods for cat2cat function - "knn", "rf", "lda".
• prune_c2c and cross_c2c to improve processing of results.
• Enable cat2cat for panel with unique identifier.
• Turn on github actions - covr, pkgdown, check.
• Preparation before R CRAN.