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High-dimensional covariance estimation / Mohsen Pourahmadi, Texas A&M University.

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Author/Creator:
Pourahmadi, Mohsen.
Language:
English.
Publication date:
2013
Copyright date:
2013
Publication:
Hoboken, New Jersey : Wiley, [2013]
Copyright notice:
©2013
Format:
  • Book
  • x, 184 pages : illustrations ; 25 cm.
Bibliography:
Includes bibliographical references (pages 171-179) and index.
Summary:
"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, [2013] 9781118573655 (DLC) 2013012679
Series:
Wiley series in probability and statistics.
Subjects:
ISBN:
9781118034293
1118034295

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