Written by two top statisticians with experience in teaching matrix methods for applications in statistics, econometrics and related areas, this book provides a comprehensive treatment of the latest techniques in matrix algebra. A well-balanced approach to discussing the mathematical theory and applications to problems in other areas is an attractive feature of the book. It can be used as a textbook in courses on matrix algebra for statisticians, econometricians and mathematicians as well. Some of the new developments of linear models are given in some detail using results of matrix algebra.
Contents: Vector SpacesUnitary and Euclidean SpacesLinear Transformations and MatricesCharacteristics of MatricesFactorization of MatricesOperations on MatricesProjectors and Idempotent OperatorsGeneralized InversesMajorizationInequalities for EigenvaluesMatrix ApproximationsOptimization Problems in Statistics and EconometricsQuadratic SubspacesInequalities with Applications in StatisticsNon-negative MatricesMiscellaneous Complements
Readership: Graduate students, researchers and scientists in economics, biology, engineering and physics.