Robust and Multivariate Statistical Methods

<p>&nbsp;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.</p>