Innovations in Multivariate Statistical Modeling

Chapter 1 Association-Based Optimal Subpopulation Selection for Multivariate Data

Chapter 2 Likelihood-Based Inference for Linear Mixed-Effects Models with Censored Response Using Skew-Normal Distribution

Chapter 3 Robust Estimation of Multiple Change Points in Multivariate Processes

Chapter 4 Some Computational Aspects of a Noncentral Dirichlet Family

Chapter 5 Modeling Handwritten Digits Dataset Using the Matrix Variate t Distribution

Chapter 6 On the Identification of Extreme Elements in a Residual for the GMANOVA-MANOVA Model

Chapter 7 Matrix-variate Smooth Transition Models for Temporal Networks

Chapter 8 A Flexible Matrix-Valued Response Regression for Skewed Data

Chapter 9 Multivariate Functional Singular Spectrum Analysis: A Nonparametric Approach for Analyzing Multivariate Functional Time Series

Chapter 10 Compositional Data Analysis—Linear Algebra, Visualization and Interpretation

Chapter 11 Multivariate Count Data Regression Models and Their Applications

Chapter 12 A Generalized Multivariate Gamma Distribution

Chapter 13 A Comparison of Different Clustering Approaches for High-Dimensional Presence-Absence Data

Chapter 14 High-Dimensional Feature Selection for Logistic Regression Using Blended Penalty Functions

Chapter 15 A Generalized Quadratic Garrote Approach Towards Ridge Regression Analysis

Chapter 16 High-Dimensional Nonlinear Optimization Problem in Semiparametric Regression Model

Chapter 17 Parsimonious Finite Mixtures of Matrix-Variate Regressions

Chapter 18 Robust Multivariate Modelling for Heterogeneous Data Sets with Mixtures of Multivariate Skew Laplace Normal Distributions

Chapter 19 Robust Estimation Through Preliminary Testing Based on the LAD-LASSO