activity
20122020
most citedOn Minimax Optimality of Sparse Bayes Predictive Density Estimates

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

stat.ME2020

Large-Scale Shrinkage Estimation under Markovian Dependence

Bowen Gang, Gourab Mukherjee, Wenguang Sun

We consider the problem of simultaneous estimation of a sequence of dependent parameters that are generated from a hidden Markov model. Based on observing a noise contaminated vect…

stat.ME2020

A Nearest-Neighbor Based Nonparametric Test for Viral Remodeling in Heterogeneous Single-Cell Proteomic Data

Trambak Banerjee, Bhaswar B. Bhattacharya, Gourab Mukherjee

An important problem in contemporary immunology studies based on single-cell protein expression data is to determine whether cellular expressions are remodeled post infection by a…

math.ST2019

Sparse Minimax Optimality of Bayes Predictive Density Estimates from Clustered Discrete Priors

Ujan Gangopadhyay, Gourab Mukherjee

We consider the problem of predictive density estimation under Kullback-Leibler loss in a high-dimensional Gaussian model with exact sparsity constraints on the location parameters…

stat.ME2018

Adaptive Sparse Estimation with Side Information

Trambak Banerjee, Gourab Mukherjee, Wenguang Sun

The article considers the problem of estimating a high-dimensional sparse parameter in the presence of side information that encodes the sparsity structure. We develop a general fr…

math.ST20171 cited

On Minimax Optimality of Sparse Bayes Predictive Density Estimates

Gourab Mukherjee, Iain M. Johnstone

We study predictive density estimation under Kullback-Leibler loss in -sparse Gaussian sequence models. We propose proper Bayes predictive density estimates and establish a…

stat.ME2016

Empirical Bayes Estimates for a 2-Way Cross-Classified Additive Model

Lawrence D. Brown, Gourab Mukherjee, Asaf Weinstein

We develop an empirical Bayes procedure for estimating the cell means in an unbalanced, two-way additive model with fixed effects. We employ a hierarchical model, which reflects ex…