Includes bibliographical references (pages 171-179) and index.
"Focusing on methodology and computation more than on theorems and proofs, this book provides computationally feasible and statistically efficient methods for estimating sparse and large covariance matrices of high-dimensional data. Extensive in breadth and scope, it features ample applications to a number of applied areas, including business and economics, computer science, engineering, and financial mathematics; recognizes the important and significant contributions of longitudinal and spatial data; and includes various computer codes in R throughout the text and on an author-maintained web site"-- Provided by publisher.
"The aim of this book is to provide computationally feasible and statistically efficient methods for estimating sparse and large covariance matrices of high-dimensional data"-- Provided by publisher.
Available in another form:
Online version: Pourahmadi, Mohsen. Modern methods to covariance estimation Hoboken, New Jersey : Wiley,  9781118573655 (DLC) 2013012679