Robust and Multivariate Statistical Methods : Festschrift in Honor of David E. Tyler / edited by Mengxi Yi, Klaus Nordhausen.

Format:

Book

Contributor:

Yi, Mengxi, editor.

Nordhausen, Klaus, editor.

Language:

English

Subjects (All):

Statistics.

Multivariate analysis.

Machine learning.

Statistical Theory and Methods.

Multivariate Analysis.

Applied Statistics.

Machine Learning.

Local Subjects:

Statistical Theory and Methods.

Multivariate Analysis.

Applied Statistics.

Machine Learning.

Physical Description:

1 online resource (XVIII, 495 p. 114 illus., 95 illus. in color.)

Edition:

1st ed. 2023.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2023.

Summary:

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.

Contents:

Part I About David E. Tyler’s Publications

An Analysis of David E. Tyler’s Publication and Coauthor Network. A Review of Tyler’s Shape Matrix and Its Extensions

Part II Multivariate Theory and Methods

On the Asymptotic Behavior of the Leading Eigenvector of Tyler’s Shape Estimator Under Weak Identifiability

On Minimax Shrinkage Estimation with Variable Selection

On the Finite-Sample Performance of Measure-Transportation-Based Multivariate Rank Tests

Refining Invariant Coordinate Selection via Local Projection Pursuit

Directional Distributions and the Half-Angle Principle

Part III Robust Theory and Methods

Power M-Estimators for Location and Scatter

On Robust Estimators of a Sphericity Measure in High Dimension

Detecting Outliers in Compositional Data Using Invariant Coordinate Selection

Robust Forecasting of Multiple Time Series with One-Sided Dynamic Principal Components

Robust and Sparse Estimation of Graphical Models Based on Multivariate Winsorization

Robustly Fitting Gaussian Graphical Models—the RPackage robFitConGraph

Robust Estimation of General Linear Mixed Effects Models

Asymptotic Behaviour of Penalized Robust Estimators in Logistic Regression When Dimension Increases

Conditional Distribution-Based Downweighting for Robust Estimation of Logistic Regression Models

Bias Calibration for Robust Estimation in Small Areas

The Diverging Definition of Robustness in Statistics and Computer Vision

Part IV Other Methods

Power Calculations and Critical Values for Two-Stage Nonparametric Testing Regimes

Data Nuggets in Supervised Learning

Improved Convergence Rates of Normal Extremes

Local Spectral Analysis of Qualitative Sequences via Minimum Description Length.

Notes:

Includes bibliographical references.

ISBN:

9783031226878

3031226879