Linear and graphical models for the multivariate complex normal distribution
This book is a comprehensive introduction to the undirected graphical models for the multivariate complex normal distribution. Distributional results of multivariate complex distributions are important tools for such a study. The theory of linear models for the multivariate complex normal distributions is obtained from the study of multivariate complex distributions. The book consists of 7 chapters and 2 appendices, the titles of which are the following: Ch. 1. Prerequisites. Ch. 2. Multivariate complex normal distribution. Ch. 3. Complex Wishart distribution and complex \(U\)-distribution. Ch. 4. Multivariate linear complex normal models. Ch. 5. Simple undirected graphs. Ch. 6. Conditional independence and Markov properties. Ch. 7. Complex normal graphical models. Appendix A. Complex matrices. Appendix B. Orthogonal projections. Although this book is the first complete presentation of the multivariate complex distributions and the first published presentation of the complex normal graphical models, it is relatively easily to read. The basic prerequisites for reading this book is acquaintance with the multivariate real normal distribution, matrix algebra, mathematical analysis, probability and statistics. I feel that the book will be very useful for many readers.
multivariate complex normal distribution
scientific article; zbMATH DE number 785407