Research Interests
Markov chain Monte Carlo, non/semi-parametric Bayesian methods,
Bayesian methods in biostatistics.
Selected Papers
- Athreya, K.B., Doss, H., and Sethuraman, J. (1996). On the
convergence of the Markov chain simulation method [PostScript] [PDF] (This paper has
appeared in Annals of Statistics, 24 69-100.)
- Doss, H., Huffer, F., and Lawson, K. (1997). Nonparametric
estimation via Gibbs sampling for coherent systems with
redundancy
[PostScript]
[PDF] (This paper has appeared in Annals of
Statistics, 25 1109-1139.)
- Li, S., Pearl, D.K., and Doss, H. (2000). Phylogenetic tree
construction using Markov chain Monte Carlo [PostScript] [PDF] (This paper has
appeared in Journal of the American Statistical
Association, 95 493-508.)
- Burr, D., Doss, H., Cooke, G.E., and Goldschmidt-Clermont,
P.J. (2003). A meta-analysis of studies on the association of
the platelet PlA polymorphism of Glycoprotein IIIa and risk of
coronary heart disease
[PostScript]
[PDF] (This paper has appeared in
Statistics in Medicine, 22 1741-1760.)
- Doss, H. and Huffer, F. (2003). Monte Carlo methods for
Bayesian analysis of survival data using mixtures of Dirichlet
process priors
[PostScript]
[PDF] (This paper has appeared in
Journal of Computational and Graphical Statistics,
12 282-307.)
- Burr, D., Doss, H. (2005). A Bayesian semi-parametric model
for random effects meta-analysis
[PostScript]
[PDF] (This has appeared in Journal of the
American Statistical Association, 100 242-251.)
- Doss, H. (2007). Some thoughts on future directions in
Bayesian model selection
[PostScript]
[PDF] (This has appeared in Statistica
Sinica, 17 413-421.)
Software
- mc-mdp-surv
Software for Monte Carlo methods for Bayesian analysis of
survival data using mixtures of Dirichlet process priors
(JCGS 2003, 282-307). This is joint work with Fred
Huffer.