4 papers
Sharp Asymptotic Minimaxity for Multiple Testing Using One-Group Shrinkage Priors
Sayantan Paul, Prasenjit Ghosh, Arijit Chakrabarti
This paper investigates asymptotic minimaxity properties of Bayesian multiple testing rules in the sparse Gaussian sequence model using a broad class of global-local scale mixtures…
Asymptotic Bayes Optimality for Sparse Count Data
Sayantan Paul, Arijit Chakrabarti
Consider a situation of analyzing high-dimensional count data containing an excess of near-zero counts with a small number of moderate or large counts. Assuming that the observatio…
Consistent Group selection using Global-local prior in High dimensional setup
Sayantan Paul, Prasenjit Ghosh, Arijit Chakrabarti
We consider the problem of model selection when grouping structure is inherent within the regressors. Using a Bayesian approach, we model the mean vector by a one-group global-loca…
Posterior Contraction rate and Asymptotic Bayes Optimality for one-group shrinkage priors in sparse normal means problem
Sayantan Paul, Arijit Chakrabarti
We consider a high-dimensional sparse normal means model where the goal is to estimate the mean vector assuming the proportion of non-zero means is unknown. We model the mean vecto…