1 citations · 2 across the 3 of their papers we have counts for
4 papers
A Three-Stage PCA Procedure for Sequentially Arriving High-Dimensional Data
Partha Sarkar, Sairam Rayapolu, Bhargab Chattopadhyay
We develop a three-stage adaptive procedure for principal component analysis (PCA) when high-dimensional observations are collected sequentially and additional sampling incurs a co…
Bayesian Graphical Models under Positivity Constraints: A Scalable Generalized Likelihood Approach
Swarnali Raha, Partha Sarkar, Sirani M. Perera +2
We develop a computationally scalable Bayesian framework for precision matrix estimation in Gaussian graphical models under total positivity constraints. To overcome the high compu…
High-Dimensional Bernstein Von-Mises Theorems for Covariance and Precision Matrices
Partha Sarkar, Kshitij Khare, Malay Ghosh +1
This paper aims to examine the characteristics of the posterior distribution of covariance/precision matrices in a "large , large " scenario, where represents the number…
Posterior consistency in multi-response regression models with non-informative priors for the error covariance matrix in growing dimensions
Partha Sarkar, Kshitij Khare, Malay Ghosh
The Inverse-Wishart (IW) distribution is a standard and popular choice of priors for covariance matrices and has attractive properties such as conditional conjugacy. However, the I…