Robust and Multivariate Statistical Methods
Festschrift in Honor of David E. Tyler
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Beschreibung
This book presents recent developments in multivariate and robust statistical methods. Featuring contributions by leading experts in the field it covers various topics, including multivariate and high-dimensional methods, time series, graphical models, robust estimation, supervised learning and normal extremes. It will appeal to statistics and data science researchers, PhD students and practitioners who are interested in modern multivariate and robust statistics. The book is dedicated to David E. Tyler on the occasion of his pending retirement and also includes a review contribution on the popular Tyler’s shape matrix.
This book presents recent developments in multivariate and robust statistical methods. Featuring contributions by leading experts in the field it covers various topics, including multivariate and high-dimensional methods, time series, graphical models, robust estimation, supervised learning and normal extremes. It will appeal to statistics and data science researchers, PhD students and practitioners who are interested in modern multivariate and robust statistics. The book is dedicated to David E. Tyler on the occasion of his pending retirement and also includes a review contribution on the popular Tyler’s shape matrix.
Presents the latest findings in multivariate and robust statistics Features contributions by leading experts in the field, including a review of Tyler’s shape matrix Fosters new directions of research
Autor*in
Mengxi Yi
Themen in »Robust and Multivariate Statistical Methods«
Multivariate Statistical Methods Robust Statistical Methods High-dimensional Methods Tyler's Shape Matrix Tyler's Shape Estimator Multivariate Analysis Robust Estimation Asymptotics Robustness Time Series Analysis Supervised Learning Graphical Models Normal Extremes