Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data
An Applied Treatment of Modern Graphical Methods for Analyzing Categorical DataDiscrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and frequency data. It explains how to use graphical meth
What people are saying - Write a review
We haven't found any reviews in the usual places.
Other editions - View all
Admit ANOVA Arthritis association binomial distribution biplot calculate categorical data cells Chapter Chisq Df Pr(>Chisq codes coefficients conditional contingency table correspondence analysis count data data frame data set default Deviance diagonal dimensions discrete distributions Donner Donner Party effect plot estimated example explanatory variables eye color factors Female fitted model Freq function gender gives graphs hair color Hazel Green independence interaction interpretation labels levels linear models log odds ratios logistic regression logit model loglinear models loglm LR Chisq Df Male marginal matrix models fit mosaic display mosaic plots negative binomial negative-binomial observed parameters Poisson distribution predictors probability relation response variable result row and column sample saturated model scores Section shading shown in Figure shows Signif statistical studentized residuals three-way table Treatment two-way table uncons urea variance vcdExtra vector visual xlab ylab zero