48 citations · 126 across the 51 of their papers we have counts for
11 papers · 1 filter
A Bayesian Semiparametric Approach to Learning About Gene-Gene Interactions in Case-Control Studies
Durba Bhattacharya, Sourabh Bhattacharya
Gene-gene interactions are often regarded as playing significant roles in influencing variabilities of complex traits. Although much research has been devoted to this area, to date…
On Single Variable Transformation Approach to Markov Chain Monte Carlo
Kushal K. Dey, Sourabh Bhattacharya
Random Walk Metropolis Hastings (RWMH) algorithm, is quite inefficient in high dimensions because of its abysmally slow acceptance rate. The slow acceptance rate results from the f…
Bayesian Nonparametric Dynamic State Space Modeling with Circular Latent States
Satyaki Mazumder, Sourabh Bhattacharya
State space models are well-known for their versatility in modeling dynamic systems that arise in various scientific disciplines. Although parametric state space models are well st…
On Bayesian Asymptotics in Stochastic Differential Equations with Random Effects
Trisha Maitra, Sourabh Bhattacharya
Delattre et al. (2013) investigated asymptotic properties of the maximum likelihood estimator of the population parameters of the random effects associated with n independent stoch…
On Asymptotics Related to Classical Inference in Stochastic Differential Equations with Random Effects
Trisha Maitra, Sourabh Bhattacharya
Delattre et al. (2013) considered n independent stochastic differential equations (SDEs), where in each case the drift term is associated with a random effect, the distribution of…
A Note on the Misuse of the Variance Test in Meteorological Studies
Arnab Hazra, Sourabh Bhattacharya, Sabyasachi Bhattacharya +1
The erroneous assumption "for all distributions for which the theoretical variance can be computed independently from parameters estimated by any method different from the method o…
Gaussian Random Functional Dynamic Spatio-Temporal Modeling of Discrete Time Spatial Time Series Data
Suman Guha, Sourabh Bhattacharya
Discrete time spatial time series data arise routinely in meteorological and environmental studies. Inference and prediction associated with them are mostly carried out using any o…
Nonstationary, Nonparametric, Nonseparable Bayesian Spatio-Temporal Modeling Using Kernel Convolution of Order Based Dependent Dirichlet Process
Moumita Das, Sourabh Bhattacharya
In this article, using kernel convolution of order based dependent Dirichlet process (Griffin and Steel (2006)) we construct a nonstationary, nonseparable, nonparametric space-time…
A Brief Review of Optimal Scaling of the Main MCMC Approaches and Optimal Scaling of Additive TMCMC Under Non-Regular Cases
Kushal Kr Dey, Sourabh Bhattacharya
Very recently, Transformation based Markov Chain Monte Carlo (TMCMC) was proposed by Dutta and Bhattcharya (2013) as a much efficient alternative to the Metropolis-Hastings algorit…
Transdimensional Transformation based Markov Chain Monte Carlo
Moumita Das, Sourabh Bhattacharya
In this article, we propose a novel and general dimension-hopping MCMC methodology that can update all the parameters as well as the number of parameters simultaneously using simpl…
Adaptive-Rate Compressive Sensing Using Side Information
Garrett Warnell, Sourabh Bhattacharya, Rama Chellappa +1
We provide two novel adaptive-rate compressive sensing (CS) strategies for sparse, time-varying signals using side information. Our first method utilizes extra cross-validation mea…