6 citations · 11 across the 12 of their papers we have counts for
7 papers · 1 filter
A Bayesian Multiple Testing Paradigm for Model Selection in Inverse Regression Problems
Debashis Chatterjee, Sourabh Bhattacharya
In this article, we propose a novel Bayesian multiple testing formulation for model and variable selection in inverse setups, judiciously embedding the idea of inverse reference di…
Convergence of Pseudo-Bayes Factors in Forward and Inverse Regression Problems
Debashis Chatterjee, Sourabh Bhattacharya
In the Bayesian literature on model comparison, Bayes factors play the leading role. In the classical statistical literature, model selection criteria are often devised used cross-…
Posterior Consistency of Bayesian Inverse Regression and Inverse Reference Distributions
Debashis Chatterjee, Sourabh Bhattacharya
We consider Bayesian inference in inverse regression problems where the objective is to infer about unobserved covariates from observed responses and covariates. We establish poste…
Posterior Convergence of Nonparametric Binary and Poisson Regression Under Possible Misspecifications
Debashis Chatterjee, Sourabh Bhattacharya
In this article, we investigate posterior convergence of nonparametric binary and Poisson regression under possible model misspecification, assuming general stochastic process prio…
High-dimensional Asymptotic Theory of Bayesian Multiple Testing Procedures Under General Dependent Setup and Possible Misspecification
Noirrit Kiran Chandra, Sourabh Bhattacharya
In this article, we investigate the asymptotic properties of Bayesian multiple testing procedures under general dependent setup, when the sample size and the number of hypotheses b…
Bayesian Characterizations of Properties of Stochastic Processes with Applications
Sucharita Roy, Sourabh Bhattacharya
In this article, we primarily propose a novel Bayesian characterization of stationary and nonstationary stochastic processes. In practice, this theory aims to distinguish between g…