Kshitij Khare

High‐dimensional covariance estimation for Gaussian directed acyclic graph models with given order

2019 · Wiley Interdisciplinary Reviews Computational Statistics

Abstract The covariance matrix is a fundamental quantity that helps us understand the nature of relationships among variables in a multivariate data set. Estimating the covariance matrix can be challenging in modern applications where the …

Scalable Bayesian shrinkage and uncertainty quantification for high-dimensional regression

2015 · arXiv (Cornell University)

Bayesian shrinkage methods have generated a lot of recent interest as tools for high-dimensional regression and model selection. These methods naturally facilitate tractable uncertainty quantification and incorporation of prior information. This benefit has led to …