Synopses & Reviews
The main purpose of Linear Algebra and Linear Models is to provide a rigorous introduction to the basic aspects of the theory of linear estimation and hypothesis testing. The necessary prerequisites in matrices, multivariate normal distribution and distributions of quadratic forms are developed along the way. The book is aimed at advanced undergraduate and first-year graduate masters students taking courses in linear algebra, linear models, multivariate analysis, and design of experiments. It should also be of use to research mathematicians and statisticians as a source of standard results and problems.
Synopsis
This book presents the linear algebra that is needed for statistical applications by providing a rigorous introduction to the basic aspects of the theory of linear estimation and hypothesis testing. All of the necessary pre-requisites are developed along the way. The book will be invaluable to research mathematicians and statisticians as a source of standard results and problems.
Synopsis
This book provides a rigorous introduction to the basic aspects of the theory of linear estimation and hypothesis testing, covering the necessary prerequisites in matrices, multivariate normal distribution and distributions of quadratic forms along the way. It will appeal to advanced undergraduate and first-year graduate students, research mathematicians and statisticians.
Table of Contents
Vector Spaces and Matrices.- Linear Estimation.- Tests of Linear Hypotheses.- Singular Values and Their Applications.- Block Designs and Optimality.- Rank Additivity.