High‐dimensional covariance estimation for Gaussian directed acyclic graph models with given order
Sign Up to like & getrecommendations! Published in 2019 at "Wiley Interdisciplinary Reviews: Computational Statistics"
DOI: 10.1002/wics.1468
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 number… read more here.
Keywords: estimation gaussian; dimensional covariance; covariance; covariance matrix ... See more keywords
Riemannian Statistics Meets Random Matrix Theory: Toward Learning From High-Dimensional Covariance Matrices
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2022.3199479
Abstract: Riemannian Gaussian distributions were initially introduced as basic building blocks for learning models which aim to capture the intrinsic structure of statistical populations of positive-definite matrices (here called covariance matrices). While the potential applications of… read more here.
Keywords: covariance matrices; dimensional covariance; random matrix; covariance ... See more keywords