Bayesian Models for Categorical Data is popular PDF and ePub book, written by Peter Congdon in 2005-12-13, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Bayesian Models for Categorical Data can be Read Online from any device for your convenience.
Bayesian Models for Categorical Data Book PDF Summary
The use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods for Categorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike. Emphasizing the use of statistical computing and applied data analysis, this book provides a comprehensive introduction to Bayesian methods of categorical outcomes. * Reviews recent Bayesian methodology for categorical outcomes (binary, count and multinomial data). * Considers missing data models techniques and non-standard models (ZIP and negative binomial). * Evaluates time series and spatio-temporal models for discrete data. * Features discussion of univariate and multivariate techniques. * Provides a set of downloadable worked examples with documented WinBUGS code, available from an ftp site. The author's previous 2 bestselling titles provided a comprehensive introduction to the theory and application of Bayesian models. Bayesian Models for Categorical Data continues to build upon this foundation by developing their application to categorical, or discrete data - one of the most common types of data available. The author's clear and logical approach makes the book accessible to a wide range of students and practitioners, including those dealing with categorical data in medicine, sociology, psychology and epidemiology.
Detail Book of Bayesian Models for Categorical Data PDF
- Author : Peter Congdon
- Release : 13 December 2005
- Publisher : John Wiley & Sons
- ISBN : 9780470092385
- Genre : Mathematics
- Total Page : 446 pages
- Language : English
- PDF File Size : 8,9 Mb
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