High-dimensional covariance matrix estimation : an introduction to random matrix theory / Aygul Zagidullina.
2021
QA276.8 .Z34 2021
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Details
Title
High-dimensional covariance matrix estimation : an introduction to random matrix theory / Aygul Zagidullina.
Author
Zagidullina, Aygul, author.
ISBN
9783030800659 (electronic bk.)
3030800652 (electronic bk.)
9783030800642
3030800644
3030800652 (electronic bk.)
9783030800642
3030800644
Published
Cham : Springer, [2021]
Copyright
©2021
Language
English
Description
1 online resource : color illustrations
Item Number
10.1007/978-3-030-80065-9 doi
Call Number
QA276.8 .Z34 2021
Dewey Decimal Classification
519.5/44
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
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Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed November 15, 2021).
Series
SpringerBriefs in applied statistics and econometrics. 2524-4124
Available in Other Form
Print version: 9783030800642
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Table of Contents
Foreword
1 Introduction
2 Traditional Estimators and Standard Asymptotics
3 Finite Sample Performance of Traditional Estimators
4 Traditional Estimators and High-Dimensional Asymptotics
5 Summary and Outlook
Appendices.
1 Introduction
2 Traditional Estimators and Standard Asymptotics
3 Finite Sample Performance of Traditional Estimators
4 Traditional Estimators and High-Dimensional Asymptotics
5 Summary and Outlook
Appendices.