3 papers
stat.ME2026
Bayesian Graphical Models under Positivity Constraints: A Scalable generalized likelihood Approach
Swarnali Raha, Partha Sarkar, Sirani Perera +1
We develop a computationally scalable Bayesian framework for precision matrix estimation in Gaussian graphical models under total positivity constraints. To overcome the high compu…
math.ST2023
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…
math.ST2023
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…