High-dimensional covariance estimation

"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...

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Auteur principal : Pourahmadi Mohsen (Auteur)
Format : Livre
Langue : anglais
Titre complet : High-dimensional covariance estimation / Mohsen Pourahmadi
Publié : Hoboken (US) : Wiley , 2013
Description matérielle : 1 vol. (X-184 p.)
Collection : Wiley series in probability and statistics
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Documents associés : Autre format: High-dimensional covariance estimation
Description
Résumé : "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"--
Bibliographie : Bibliogr. p. 171-179. Index
ISBN : 978-1-11-803429-3