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Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multiv

This book presents covariance matrix estimation and related aspects of random matrix theory. It focuses on the sample covariance matrix estimator and provides a

An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

High-dimensional data appear in many fields, and their analysis has become increasingly important in modern statistics. However, it has long been observed that

Large Covariance and Autocovariance Matrices brings together a collection of recent results on sample covariance and autocovariance matrices in high-dimensional