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Matrix Analysis for Statistics, Third Edition (Wiley Series in Probability and Statistics)
Matrix Analysis for Statistics Third Edition - Wiley Series in Probability and Statistics Author:James R. Schott This volume provides in-depth, step-by-step coverage of the most common matrix methods now used in statistical applications, including eigenvalues and eigenvectors; the Moore-Penrose inverse; matrix differentiation; the distribution of quadratic forms; and more. The subject matter is presented in a theorem/proof format, and every effort has been... more » made to ease the transition from one topic to another. Proofs are easy to follow, and the author carefully justifies every step. Accessible even for readers with a cursory background in statistics, the text uses examples that are familiar and easy to understand. Key features that make this the ideal introduction to matrix analysis theory and practice include: self-contained chapters for flexibility in topic choice, extensive examples and chapter-end practice exercises, and optional sections for mathematically advanced readers.
The third edition includes a new chapter on inequalities. Numerous inequalities (e.g. Cauchy-Schwarz, Hadamard, Jensen?s) already appear in the current text, but there are many important ones that are missing and some of these are given in the new chapter. Highlighting this chapter is a fairly substantial section on majorization and some of the inequalities that can be developed from this concept. It also includes a new section in Chapter 2 on oblique projections and their projection matrices and a new section in Chapter 3 on antieigenvalues and antieigenvectors. Finally, new theorems, proofs, examples and problems are included throughout the text.« less