Description
Wiley India Pvt Ltd Bayesian Models For Categorical Data by Congdon Peter
About the Book: Bayesian Models for Categorical DataCategorical, or discrete, data is one of the most common types of data available Bayesian methods are increasingly being used for the modeling of such data, yet there is no book available that provides an overview of Bayesian models for analyzing categorical data The proposed book would provide such an overview, together with a huge number of worked examples to illustrate the methods WinBUGS code for the examples will be made available via ftp, so that the reader can apply the methods to their own data The book also includes exercises that require the student to do further analysis of the included examples, and enabling use of the book as a course textContentsPrefaceChapter 1 Principles of Bayesian InferenceChapter 2 Model Comparison and ChoiceChapter 3 Regression for Metric OutcomesChapter 4; Models for Binary and Count OutcomesChapter 5 Further Questions in Binomial and Count RegressionChapter 6 Random Effect and Latent Variable Models for Multicategory OutcomesChapter 7 Ordinal RegressionChapter 8 Discrete Spatial DataChapter 9 Time Series Models for Discrete VariablesChapter 10 Hierarchical and Panel Data ModelsChapter 11 Missing-Data ModelsExercisesReferencesIndexAbout the Author: Peter CongdonPeter Congdon, Queen Mary, University of London, UK Peter is the author of two best-selling Wiley books on Bayesian modelling - Bayesian Statistical Modelling and Applied Bayesian Modelling.