High-Dimensional Covariance Matrix Estimation (eBook)

An Introduction to Random Matrix Theory

Aygul Zagidullina (Autor)

eBook Download: PDF

2021 | 1st ed. 2021
XIV, 115 Seiten
Springer International Publishing (Verlag)
978-3-030-80065-9 (ISBN)

Infos

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.

Aygul Zagidullina received her Ph.D. in Quantitative Economics and Finance from the University of Konstanz, Germany, with a specialization in the areas of financial econometrics and statistical modeling. Her research interests include estimation of high-dimensional covariance matrices, machine learning, factor models and neural networks.

Produkt-Details

• Erscheint lt. Verlag: 29.10.2021
• Reihe/Serie: SpringerBriefs in Applied Statistics and Econometrics
• Reihe/Serie: SpringerBriefs in Applied Statistics and Econometrics
• Zusatzinfo: XIV, 115 p. 26 illus. in color.
• Sprache: englisch
• Original-Titel: Three Essays on Covariance Matrix Estimation and Factor Models in High Dimensions
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Themenwelt: Wirtschaft ► Allgemeines / Lexika
• Schlagworte: Big Data • covariance matrix estimation • High-dimensional Asymptotics • high-dimensional covariance matrix estimation • High-Dimensional Statistics • linear spectral statistics for high-dimensional inference • Random Matrix Theory • sample covariance matrix estimator • shrinkage estimation of covariance matrices • Statistical Inference
• ISBN-10: 3-030-80065-2 / 3030800652
• ISBN-13: 978-3-030-80065-9 / 9783030800659