Visualizing Categorical Data
Bangdiwala's Observer Agreement Chart
Extended Association Plots
Association Statistics
Binary Regression Plot
Conditional Density Plots
Compute Conditional Tables
Test for (Conditional) Independence
Panel-generating Functions for Contingency Table Coplots
Coplot for Contingency Tables
Diagnostic Distribution Plots
Doubledecker Plot
Fourfold Plots
Goodness-of-fit Tests for Discrete Data
Barplot
Legend Function for grid Graphics
HLS Color Specification
Independence Table
Cohen's Kappa and Weighted Kappa
Labeling Functions for Strucplots
Labeling Functions for Strucplots
Legend Functions for Strucplots
Calculate Generalized Log Odds for Frequency Tables
Calculate Generalized Log Odds Ratios for Frequency Tables
Table with Marginal Sums
Extended Mosaic Plots
Multiple Grid plots
Ord Plots
Pairs Plot for Contingency Tables
Diagonal Panel Functions for Table Pairs Plot
Off-diagonal Panel Functions for Table Pairs Plot
Plotting (Log) Odds Ratios
Visualize Fitted Log-linear Models
Rootograms
Shading-generating Functions for Residual-based Shadings
Extended Sieve Plots
Spacing-generating Functions
Spine Plots and Spinograms
Core-generating Function for Association Plots
Core-generating Function for Mosaic Plots
Core-generating Function for Sieve Plots
Structured Displays of Contingency Tables
Structured Contingency Tables
Summary of a 2-way Table
Ternary Diagram
Tile Plot
Woolf Test
Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).