Methods and utilities for testing, identifying, selecting and  
    mutating objects as categorical or continous types. These functions work on both 
    atomic vectors as well as recursive objects: data.frames, data.tables, 
    tibbles, lists, etc..

Categorical data analysis by AIC. The methodology is described in
 Sakamoto (1992) <ISBN 978-0-7923-1429-5>.

This R-package contains examples from the book "Regression for Categorical Data", Tutz 2012, Cambridge University Press. The names of the examples refer to the chapter and the data set that is used.

Datasets used in the book "Categorical Data Analysis"
   by Agresti (2012, ISBN:978-0-470-46363-5) but not printed in the book.
   Datasets and help pages were automatically produced from the source
   <https://users.stat.ufl.edu/~aa/cda/data.html> by the R script foo.R,
   which can be found in the GitHub repository.

Based on fishery Catch Dynamics instead of fish Population Dynamics (hence CatDyn) and using high-frequency or medium-frequency catch in biomass or numbers, fishing nominal effort, and mean fish body weight by time step, from one or two fishing fleets, estimate stock abundance, natural mortality rate, and fishing operational parameters. It includes methods for data organization, plotting standard exploratory and analytical plots, predictions, for 100 types of models of increasing complexity, and 72 likelihood models for the data.

Simple, fast, and automatic encodings for category data using 
             a data.table backend. Most of the methods are an implementation 
             of "Sufficient Representation for Categorical Variables" by
             Johannemann, Hadad, Athey, Wager (2019) <arXiv:1908.09874>,
             particularly their mean, sparse principal component analysis, 
             low rank representation, and multinomial logit encodings.

Provides a 'Shiny' application and supporting functions for the 
          design and analysis of consistency tests based on Kappa statistic with
          categorical responses. Wraps 'irr' and 'kappaSize' packages.