48 citations · 126 across the 51 of their papers we have counts for
8 papers · 1 filter
IID Sampling from Posterior Dirichlet Process Mixtures
Sourabh Bhattacharya
The influence of Dirichlet process mixture is ubiquitous in the Bayesian nonparametrics literature. But sampling from its posterior distribution remains a challenge, despite the ad…
IID Sampling from Doubly Intractable Distributions
Sourabh Bhattacharya
Intractable posterior distributions of parameters with intractable normalizing constants depending upon the parameters are known as doubly intractable posterior distributions. The…
IID Sampling from Intractable Distributions
Sourabh Bhattacharya
We propose a novel methodology for drawing iid realizations from any target distribution on the Euclidean space with arbitrary dimension. No assumption of compact support is necess…
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…
Supplement to "Markov Chain Monte Carlo Based on Deterministic Transformations"
Somak Dutta, Sourabh Bhattacharya
This is a supplement to the article "Markov Chain Monte Carlo Based on Deterministic Transformations" available at http://arxiv.org/abs/1106.5850
Markov Chain Monte Carlo Based on Deterministic Transformations
Somak Dutta, Sourabh Bhattacharya
In this article we propose a novel MCMC method based on deterministic transformations T: X x D --> X where X is the state-space and D is some set which may or may not be a subset o…
Perfect Simulation for Mixtures with Known and Unknown Number of components
Sabyasachi Mukhopadhyay, Sourabh Bhattacharya
We propose and develop a novel and effective perfect sampling methodology for simulating from posteriors corresponding to mixtures with either known (fixed) or unknown number of co…