## Research interests

Convergence rates of Markov chain Monte Carlo algorithms, model
selection, spatial statistics, survival analysis, Bayes and empirical
Bayes methods

## Papers

- Athreya, K. B. and Roy, V. (2015) Estimation of integrals with respect to infinite measures using regenerative sequences,
* Journal of Applied Probability, * * to appear*
pdf

- Athreya, K. B. and Roy, V. (2014) Monte Carlo methods for improper target
distributions,
* Electronic Journal of
Statistics, * ** 8 ** 2664-2692 pdf

- Roy, V., Evangelou, E. and Zhou Z. (2014) Empirical Bayes methods
for the transformed Gaussian random field model with additive measurement
errors,
* Current Trends in Bayesian Methodology with Applications, *
S. K. Upadhyay, U. Singh, D. K. Dey and A. Loganathan, eds. Chapman & Hall/CRC Press, In Press

- Roy, V. (2014) Efficient estimation of the link function
parameter in a robust Bayesian binary regression model,
*
Computational Statistics and Data Analysis, * ** 73 ** 87-102
pdf

- Athreya, K. B. and Roy, V. (2014) When is a Markov chain regenerative?,
* Statistics and Probability Letters, * ** 84 ** 22-26
pdf

- Roy, V. and Dey, D. K. (2014) Propriety of posterior distributions arising in categorical and survival models under generalized extreme value distribution,
* Statistica Sinica, * ** 24 ** 699-722
pdf

- Roy, V. and Kaiser, M. S. (2013) Posterior propriety for Bayesian binomial regression models with a parametric family of link functions,
* Statistical Methodology, * ** 13 ** 25-41
pdf

- Roy, V. (2012) Convergence rates for MCMC algorithms for a robust
Bayesian binary regression model,
* Electronic Journal of
Statistics, * ** 6 ** 2463-2485 pdf

- Roy, V. (2012) Spectral analytic comparisons for Data Augmentation,
* Statistics and Probability Letters, * ** 82 ** 103-108
pdf

- Hobert, J. P. ,Roy, V. and Robert, C. P.(2011). Improving the convergence properties of the data
augmentation algorithm with an application to Bayesian mixture
modelling,
* Statistical Science *,** 26** 332-351 pdf

- Roy, V. and Hobert, J. P. (2010) On Monte Carlo methods for Bayesian
multivariate regression models with heavy-tailed
errors,
* Journal of Multivariate
Analysis*,** 101** 1190-1202 pdf

- Roy, V. and Hobert, J. P. (2007) Convergence rates and asymptotic
standard errors for MCMC algorithms for Bayesian probit
regression,
* Journal of the Royal Statistical Society,
Series B *, ** 69 ** 607-623 pdf

## Invited Book Review

Roy, V. (2012) "Handbook of Markov chain Monte Carlo"
edited by S. P. Brooks, A. Gelman, G. L. Jones and X.-L. Meng, *Journal
of the American Statistical Association,* ** 107 ** 434-435

## Software

** geoBayes ** * It is an R package for Bayes and empirical Bayes analysis of geostatistical data and is available at CRAN. *
This is joint work with E. Evangelou.