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πŸ“

Practical Nonparametric and Semiparametric Bayesian Statistics

✍ Scribed by Michael D. Escobar, Mike West (auth.), Dipak Dey, Peter Müller, Debajyoti Sinha (eds.)


Publisher
Springer-Verlag New York
Year
1998
Tongue
English
Leaves
375
Series
Lecture Notes in Statistics 133
Edition
1
Category
Library

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✦ Synopsis


A compilation of original articles by Bayesian experts, this volume presents perspectives on recent developments on nonparametric and semiparametric methods in Bayesian statistics. The articles discuss how to conceptualize and develop Bayesian models using rich classes of nonparametric and semiparametric methods, how to use modern computational tools to summarize inferences, and how to apply these methodologies through the analysis of case studies.

✦ Table of Contents


Front Matter....Pages i-xvi
Computing Nonparametric Hierarchical Models....Pages 1-22
Computational Methods for Mixture of Dirichlet Process Models....Pages 23-43
Nonparametric Bayes methods using predictive updating....Pages 45-61
Dynamic Display of Changing Posterior in Bayesian Survival Analysis....Pages 63-87
Semiparametric Bayesian Methods for Random Effects Models....Pages 89-114
Nonparametric Bayesian Group Sequential Design....Pages 115-132
Wavelet-Based Nonparametric Bayes Methods....Pages 133-155
Nonparametric Estimation of Irregular Functions with Independent or Autocorrelated Errors....Pages 157-179
Feedforward Neural Networks for Nonparametric Regression....Pages 181-193
Survival Analysis Using Semiparametric Bayesian Methods....Pages 195-211
Bayesian Nonparametric and Covariate Analysis of Failure Time Data....Pages 213-225
Simulation of LΓ©vy Random Fields....Pages 227-242
Sampling Methods For Bayesian Nonparametric Inference Involving Stochastic Processes....Pages 243-254
Curve and Surface Estimation Using Dynamic Step Functions....Pages 255-272
Prior Elicitation for Semiparametric Bayesian Survival Analysis....Pages 273-292
Asymptotic Properties of Nonparametric Bayesian Procedures....Pages 293-304
Modeling Travel Demand in Portland, Oregon....Pages 305-322
Semiparametric PK/PD Models....Pages 323-337
A Bayesian Model for Fatigue Crack Growth....Pages 339-353
A Semiparametric Model for Labor Earnings Dynamics....Pages 355-369
Back Matter....Pages 370-371

✦ Subjects


Statistics, general


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