Practical Nonparametric and Semiparametric Bayesian Statistics

I. DIRICHLET AND RELATED PROCESSES,
1. Computing Nonparametric Hierarchical Models, M. Escobar and M. West;
2. Computational Methods for Mixture of Dirichlet Process Models, S. MacEachern;
3. Nonparametric Bayes Methods Using Predictive Updating, M. Newton, F.A. Quintana and Y. Zhang;
4. Dynamic Display of Changing Posterior in Bayesian Survival Analysis, H. Doss and B. Narasimhan;
5. Semiparametric Bayesian Methods for Random Effects Models, K. Kleinman and J. Ibrahim;
6. Nonparametric Bayesian Group Sequential Design, P. Vlachos and A. Gelfand;

II. MODELING RANDOM FUNCTIONS,
7. Wavelet- Based Nonparametric Bayes Methods, B. Vidakovic;
8. Nonparametric Estimation of Irregular Functions With Independent or Autocorrelated Errors, M. Smith and R. Kohn;
9. Feedforward Neural Networks for Nonparametric Regression, D. Rios Insua and P. Muller;

III. LEVY AND RELATED PROCESSES,
10. Survival Analysis Using Semiparametric Bayesian Methods, D. Sinha and D. Dey;
11. Bayesian Nonparametric and Covariate Analysis of Failure Time Data, P.W. Laud, P. Damien and A.F.M. Smith;
12. Simulation of Levy Random Fields, R.L. Wolpert and K. Ickstadt;
13. Sampling Methods For Bayesian Nonparametric Inference Involving

Dipak K. Dey is Head and Professor of Statistics at the University of Connecticut.