Estimation of variances and covariances for high‐dimensional data: a selective review

Abstract

Estimation of variances and covariances is required for many statistical methods such as t‐test, principal component analysis and linear discriminant analysis. High‐dimensional data such as gene expression microarray data and financial data pose challenges to traditional statistical and computational methods. In this paper, we review some recent developments in the estimation of variances, covariance matrix, and precision matrix, with emphasis on the applications to microarray data analysis. WIREs Comput Stat 2014, 6:255–264. doi: 10.1002/wics.1308This article is categorized under: Data: Types and Structure > Microarrays Statistical and Graphical Methods of Data Analysis > Multivariate Analysis