Textbook Of Matrix Algebra
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TEXTBOOK OF MATRIX ALGEBRA
Author: BISWAS, SUDDHENDU
language: en
Publisher: PHI Learning Pvt. Ltd.
Release Date: 2012-08-07
Intended as a text for postgraduate and undergraduate honours students of Statistics, Mathematics, Operations Research as well as students in various branches of Engineering, this student-friendly book gives an indepth analysis of Matrix Algebra and all the major topics related to it. Divided into 12 chapters, the book begins with a discussion on Elements of Matrix Theory and Some Special Matrices. Then it goes on to give a detailed discussion on Scalar Function and Inverse of a Matrix, Rank of a Matrix, Generalized Inverse of a Matrix, and Quadric Forms and Inequalities. The book concludes by giving Some Applications of Algebra of Matrices, Matrices in the Infinite Dimensional Vector Space, and Computational Tracts in Matrices. KEY FEATURES Gives a large number of both solved and unsolved problems of Elementary Matrix. Provides an exhaustive treatment of Generalized Inverse Matrix with many applications in Statistics. Devotes one chapter exclusively to application of Matrices. Provides one full chapter on Matrices in the Infinite Dimensional Vector Space, which will be quite useful for postgraduate students. Gives an Appendix on R Software which will be extremely useful for students of Statistics. Provides Question Bank which will greatly benefit both undergraduate and postgraduate students. This book, which beautifully blends both theory and applications of Matrix Algebra, should prove to be an invaluable text for the students.
Matrix Algebra
Author: James E. Gentle
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-08-06
Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. The first part of this book presents the relevant aspects of the theory of matrix algebra for applications in statistics. This part begins with the fundamental concepts of vectors and vector spaces, next covers the basic algebraic properties of matrices, then describes the analytic properties of vectors and matrices in the multivariate calculus, and finally discusses operations on matrices in solutions of linear systems and in eigenanalysis. This part is essentially self-contained. The second part of the book begins with a consideration of various types of matrices encountered in statistics, such as projection matrices and positive definite matrices, and describes the special properties of those matrices. The second part also describes some of the many applications of matrix theory in statistics, including linear models, multivariate analysis, and stochastic processes. The brief coverage in this part illustrates the matrix theory developed in the first part of the book. The first two parts of the book can be used as the text for a course in matrix algebra for statistics students, or as a supplementary text for various courses in linear models or multivariate statistics. The third part of this book covers numerical linear algebra. It begins with a discussion of the basics of numerical computations, and then describes accurate and efficient algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors. Although the book is not tied to any particular software system, it describes and gives examples of the use of modern computer software for numerical linear algebra. This part is essentially self-contained, although it assumes some ability to program in Fortran or C and/or the ability to use R/S-Plus or Matlab. This part of the book can be used as the text for a course in statistical computing, or as a supplementary text for various courses that emphasize computations. The book includes a large number of exercises with some solutions provided in an appendix.
Matrix Algebra
Author: Karim M. Abadir
language: en
Publisher: Cambridge University Press
Release Date: 2005-08-22
Matrix Algebra is the first volume of the Econometric Exercises Series. It contains exercises relating to course material in matrix algebra that students are expected to know while enrolled in an (advanced) undergraduate or a postgraduate course in econometrics or statistics. The book contains a comprehensive collection of exercises, all with full answers. But the book is not just a collection of exercises; in fact, it is a textbook, though one that is organized in a completely different manner than the usual textbook. The volume can be used either as a self-contained course in matrix algebra or as a supplementary text.