Serge B. Provost – författare

This monograph deals with bilinear forms in real random vectors and their generalizations. The authors show how zonal polynomials may be used to analyze such forms and thus to apply these concepts in a variety of statistical settings. Assuming a graduate-level background in statistics, this account is self-contained and each chapter concludes with exercises making the book ideal for a researcher seeking a straight-forward introduction to this topic. Chapter 1 covers preliminaries including a treatment of the Jacobians of matrix transformation and chapter 2 then introduces bilinear forms in Gaussian random real vectors. Chapter 3 covers quadratic forms in elliptically contoured and spherically symmetric vectors whilst chapters 4 and 5 introduce and then apply the theory of zonal polynomials to the theory of distributions of generalized quadratic and bilinear forms.

This book explores topics in multivariate statistical analysis, relevant in the real and complex domains. It utilizes simplified and unified notations to render the complex subject matter both accessible and enjoyable, drawing from clear exposition and numerous illustrative examples. The book features an in-depth treatment of theory with a fair balance of applied coverage, and a classroom lecture style so that the learning process feels organic. It also contains original results, with the goal of driving research conversations forward.This will be particularly useful for researchers working in machine learning, biomedical signal processing, and other fields that increasingly rely on complex random variables to model complex-valued data. It can also be used in advanced courses on multivariate analysis. Numerous exercises are included throughout.