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(Ebook) High-Dimensional Covariance Matrix Estimation: An Introduction to Random Matrix Theory by Aygul Zagidullina ISBN 9783030800642, 3030800644

  • SKU: EBN-35997430
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Authors:Aygul Zagidullina
Pages:129 pages.
Year:2021
Editon:1
Publisher:Springer
Language:english
File Size:5.25 MB
Format:pdf
ISBNS:9783030800642, 3030800644
Categories: Ebooks

Product desciption

(Ebook) High-Dimensional Covariance Matrix Estimation: An Introduction to Random Matrix Theory by Aygul Zagidullina ISBN 9783030800642, 3030800644

This book presents covariance matrix estimation and related aspects of random matrix theory. It focuses on the sample covariance matrix estimator and provides a holistic description of its properties under two asymptotic regimes: the traditional one, and the high-dimensional regime that better fits the big data context. It draws attention to the deficiencies of standard statistical tools when used in the high-dimensional setting, and introduces the basic concepts and major results related to spectral statistics and random matrix theory under high-dimensional asymptotics in an understandable and reader-friendly way. The aim of this book is to inspire applied statisticians, econometricians, and machine learning practitioners who analyze high-dimensional data to apply the recent developments in their work.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

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