Martin Tanner Professor of Statistics

Research Interests

My research interests include Markov chain Monte Carlo methods for Bayesian and frequentist inference, nonparametric estimation of the hazard function for right-censored and interval-censored data, methodology for ecological Inference, applications of multiple imputation to censored regression data, as well as models and measures of interrater agreement/ disagreement. My recent work considers the use of Bayesian inference in mixtures-of-experts and hierarchical mixtures-of-experts neural network architectures.

Recent Publications

Mixtures of marginal models (with Ori Rosen and Wenxin Jiang) Biometrika 87 (2000), 391-404.

Binomial-beta hierarchical models for ecological inference (with Gary King and Ori Rosen) Sociological Methods and Research 28 (1999), 61-90.

Bayesian inference in mixtures-of-experts and hierarchical mixtures-of-experts models with an application to speech recognition (with F. Peng and R. Jacobs). Journal of the American Statistical Association 91 (1996), 953-960.

Tools for Statistical Inference: Methods for the Exploration of Posterior Distributions and Likelihood Functions (1996), Springer-Verlag, 3rd ed. 

The calculation of posterior distributions by data augmentation (with discussion) (with W H. Wong). Journal of the American Statistical Association 82 (1987), 528-50.