36 citations · 65 across the 13 of their papers we have counts for
6 papers · 1 filter
Coupling-based convergence assessment of some Gibbs samplers for high-dimensional Bayesian regression with shrinkage priors
Niloy Biswas, Anirban Bhattacharya, Pierre E. Jacob +1
We consider Markov chain Monte Carlo (MCMC) algorithms for Bayesian high-dimensional regression with continuous shrinkage priors. A common challenge with these algorithms is the ch…
Nonparametric Bayesian Deconvolution of a Symmetric Unimodal Density
Ya Su, Anirban Bhattacharya, Yan Zhang +2
We consider nonparametric measurement error density deconvolution subject to heteroscedastic measurement errors as well as symmetry about zero and shape constraints, in particular…
Efficient Bayesian shape-restricted function estimation with constrained Gaussian process priors
Pallavi Ray, Debdeep Pati, Anirban Bhattacharya
This article revisits the problem of Bayesian shape-restricted inference in the light of a recently developed approximate Gaussian process that admits an equivalent formulation of…
A Modified Sequential Probability Ratio Test
Sandipan Pramanik, Valen E. Johnson, Anirban Bhattacharya
We describe a modified sequential probability ratio test that can be used to reduce the average sample size required to perform statistical hypothesis tests at specified levels of…
Signal Adaptive Variable Selector for the Horseshoe Prior
Pallavi Ray, Anirban Bhattacharya
In this article, we propose a simple method to perform variable selection as a post model-fitting exercise using continuous shrinkage priors such as the popular horseshoe prior. Th…
Empirical Bayes, SURE and Sparse Normal Mean Models
Xianyang Zhang, Anirban Bhattacharya
This paper studies the sparse normal mean models under the empirical Bayes framework. We focus on the mixture priors with an atom at zero and a density component centered at a data…