Subharup Guha
Assistant
Professor
University of
Missouri-Columbia
209C
Middlebush Hall
Columbia,
MO 65211-6100
Email : GuhaSu AT Missouri.edu
Phone: (573) 882-5486
Fax: (573) 884-5524
Teaching
Stat 4710/7710 Introduction
to Mathematical Statistics
Stat 4830/7830 Categorical
Data Analysis
Stat 4750/7750 Introduction
to Probability Theory
Publications
Guha S. (2009). Bayesian Hidden Markov Modeling of Array CGH Data. Bayesian Modeling in
Bioinformatics (eds. Dey, D. K., Ghosh, S. and Mallick, B.), Chapman & Hall/CRC, to appear.
Guha S., Ryan L. and Morara
M. (2009).
Gauss-Seidel Estimation of Generalized Linear Mixed Models
with Application to Poisson Modeling of Spatially Varying Disease Rates.
Journal of Computational and Graphical Statistics,
to appear.
Guha S. (2008). Posterior Simulation in the Generalized Linear Mixed
Model with Semiparametric Random Effects. Journal of Computational and Graphical Statistics,
Volume 17, 410 - 425.
Guha S., Y. Li and D. Neuberg (2008). Bayesian Hidden Markov Modeling of Array CGH Data. Journal of the American Statistical Association, Volume
103, 485 - 497.
Guha S.
and S. N. MacEachern (2006). Generalized Post-stratification and
Importance Sampling for Subsampled Markov Chain Monte
Carlo Estimation. Journal of the American Statistical Association, Volume 101, 1175 - 1184.
Li,
Y., R. Tiwari R., and S. Guha, (2006). Mixture Cure Survival
Models with Dependent Censoring. Journal
of the Royal Statistical Society - Series B, Volume 69, 285 - 306.
Burden S., S. Guha, G. Morgan, L. Ryan, and L. Young (2005). Spatio-temporal
Analysis of Ischemic Heart Disease in NSW, Australia. Environmental and Ecological Statistics,
Volume 12, 427 - 448.
Guha S., S. N. MacEachern and M. Peruggia
(2004). Benchmark Estimation for Markov Chain Monte Carlo
Samples. Journal of Computational and Graphical Statistics,
Volume 13, 683 - 701.
MacEachern S.
N., M. Peruggia and S. Guha
(2003). Discussion of “A theory of
statistical models for Monte Carlo integration” by Kong, McCullagh,
Nicolae, Tan and Meng. Journal
of the Royal Statistical Society - Series B, Volume 65, 612.