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

Roy, V., Tan, A. , and Flegal, J. (2017+) Estimating standard errors for importance sampling estimators with multiple Markov chains, Statistica Sinica, to appear pdf Supplementary material

Laha, A. , Dutta, S. and Roy V. (2017+) A novel sandwich algorithm for empirical Bayes analysis of rank data, Statistics and its Interface, to appear pdf
 Roy, V., and Chakraborty, S. (2017+) Selection of tuning parameters, solution paths and standard errors for Bayesian lassos, Bayesian Analysis , to appear pdf Supplementary material
 Simpson, M. , J. Niemi, and Roy, V. (2017) Interweaving Markov chain Monte Carlo
strategies for efficient estimation of dynamic linear models, Journal of Computational and Graphical Statistics, 26 152159 pdf

Athreya, K. B. and Roy, V. (2016) General GlivenkoCantelli theorems, Stat , 5 306311 pdf
 Roy, V. (2016) Improving efficiency of data augmentation algorithms using Peskun's theorem,
Computational Statistics, 31 709728
pdf
 Roy, V., Evangelou, E. and Zhou Z. (2016) Efficient estimation and prediction for the Bayesian binary spatial model with flexible link functions, Biometrics, 72 289298 pdf Supplementary material
 Roy, D., Roy, V., and Dey, D. K. (2015)
Analysis of bivariate survival data based on copulas with log generalized extreme value
marginals, Extreme Value Modeling and Risk Analysis: Methods and
Applications D. K. Dey and J. Yan, eds. Chapman \& Hall/CRC Press, In Press
 Athreya, K. B., Normand, R., Roy, V., and Wu, S.J. (2015) Limit theorems for the estimation of L1 integrals using the Brownian motion, Statistics and Probability Letters, 100 4247 pdf
 Athreya, K. B. and Roy, V. (2015) Estimation of integrals with respect to infinite measures using regenerative sequences, Journal of Applied Probability, 52 11331145
pdf
 Roy, V., Evangelou, E. and Zhou Z. (2015) 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, 521536 pdf
 Athreya, K. B. and Roy, V. (2014) Monte Carlo methods for improper target
distributions, Electronic Journal of Statistics, 8 26642692 pdf
 Roy, V. (2014) Efficient estimation of the link function
parameter in a robust Bayesian binary regression model,
Computational Statistics and Data Analysis, 73 87102
pdf
 Athreya, K. B. and Roy, V. (2014) When is a Markov chain regenerative?, Statistics and Probability Letters, 84 2226
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 699722
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 2541
pdf
 Roy, V. (2012) Convergence rates for MCMC algorithms for a robust
Bayesian binary regression model, Electronic Journal of Statistics, 6 24632485 pdf
 Roy, V. (2012) Spectral analytic comparisons for Data Augmentation, Statistics and Probability Letters, 82 103108
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 332351 pdf
 Roy, V. and Hobert, J. P. (2010) On Monte Carlo methods for Bayesian
multivariate regression models with heavytailed
errors, Journal of Multivariate
Analysis, 101 11901202 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 607623 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 434435
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.