Download Bayesian Models for Categorical Data (Wiley Series in by Peter Congdon PDF

By Peter Congdon

Utilizing Bayesian tips on how to study information has develop into universal in utilized information, social sciences, and drugs, in addition to different disciplines requiring shut paintings with a various set of information. during this undergraduate textual content, Congdon (Queen Mary collage, U. of London) takes a realistic and available process, concentrating on statistical computing and utilized info as he covers the rules of Bayesian inference, version comparability and selection, regression for metric results, types for binary and count number results, random impact and latent variable versions for multi-category results, ordinal regression, discrete spatial info, time sequence types for discrete variables, hierarchical and panel info types and missing-data types.

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1998) Simulation methods for model criticism and robustness analysis. In Bayesian Statistics 6, Bernardo, J. ). Oxford University Press: Oxford. Gilks, W. (1996) Full conditional distributions. , Richardson, S. and Spiegelhalter, D. (eds). Chapman and Hall: London, 75–88. 26 PRINCIPLES OF BAYESIAN INFERENCE Gilks, W. and Wild, P. (1992) Adaptive rejection sampling for Gibbs sampling. Applied Statistics, 41, 337–348. , Richardson, S. and Spiegelhalter, D. (eds) (1996a) Markov Chain Monte Carlo in Practice.

Geweke, J. (1998) Simulation methods for model criticism and robustness analysis. In Bayesian Statistics 6, Bernardo, J. ). Oxford University Press: Oxford. Gilks, W. (1996) Full conditional distributions. , Richardson, S. and Spiegelhalter, D. (eds). Chapman and Hall: London, 75–88. 26 PRINCIPLES OF BAYESIAN INFERENCE Gilks, W. and Wild, P. (1992) Adaptive rejection sampling for Gibbs sampling. Applied Statistics, 41, 337–348. , Richardson, S. and Spiegelhalter, D. (eds) (1996a) Markov Chain Monte Carlo in Practice.

Journal of the Royal Statistical Society, 57B, 99–138. , Guallar, E. and Coresh, J. (2003) Transition models for change-point estimation in logistic regression. Statistics in Medicine, 22, 1141–1162. Rannala, B. (2002) Identifiability of parameters in MCMC Bayesian inference of phylogeny. Systematic Biology, 51, 754–760. Robert, C. (1996) Mixtures of distributions: inference and estimation. , Richardson, S. and Spiegelhalter, D. (eds). Chapman and Hall: London, 441–464. Roberts, C. (1996) Markov chain concepts related to sampling algorithms.

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