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Description
This volume is a tribute to Professor Dietrich von Rosen on the occasion of his 65th birthday. It contains a collection of twenty original papers. The contents of the papers evolve around multivariate analysis and random matrices with topics such as high-dimensional analysis, goodness-of-fit measures, variable selection and information criteria, inference of covariance structures, the Wishart distribution and growth curve models.
Table of Contents
- Spectral Analysis of Large Reflexive Generalized Inverse and Moore-Penrose Inverse Matrices. - Testing for Double Complete Symmetry. - Convexity of Sets Under Normal Distribution in the Structural Alloy Steel Standard. - Comments on Maximum Likelihood Estimation and Projections Under Multivariate Statistical Models. - Growth Curve Model with Orthogonal Covariance Structure. - Holonomic Gradient Method for the Cumulative Distribution Function of the Largest Eigenvalue of a Complex Wishart Matrix with NoncentralityMatrix of Rank One. - Some Tests for the Extended Growth Curve Model and Applications in the Analysis of Clustered Longitudinal Data. - Properties of BLUEs and BLUPs in Full vs. Small Linear Models with New Observations. - A Collection of Moments of theWishart Distribution. - Risk and Bias in Portfolio Optimization. - Approximating Noncentral Chi-Squared to the Moments and Distribution of the Likelihood Ratio Statistic for Multinomial Goodness of Fit. - Covariance Structure Tests for t -distribution. - Variable Selection in Joint Mean and Covariance Models. - On Shrinkage Estimators and “Effective Degrees of Freedom”. - On Explicit Estimation of the Growth Curve Model with a Block Circular Covariance Structure. - Space Decomposition and Estimation in Multivariate Linear Models. - Detection of Sparse and Weak Effects in High-Dimensional Feature Space, with an Application to Microbiome Data Analysis. - Exploring Consistencies of Information Criterion and Test-Based Criterion for High-Dimensional Multivariate Regression Models Under Three Covariance Structures. - Mean Value Test for Three-Level Multivariate Observations with Doubly Exchangeable Covariance Structure. - Estimation of the Common Mean of Two Multivariate Normal Distributions Under Symmetrical and Asymmetrical Loss Functions.
