Gentle J Numerical Linear Algebra For Applications in Statistics 1998 | 5.68 MB
English | 232 Pages

Title: C:\Books_Current\NLAbk\First\2ndPrint\Linbook.dvi
Author: James E. Gentle
Year: 2007

Description:
Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. This much-needed work presents the relevant aspects of the theory of matrix algebra for applications in statistics. It moves on to consider the various types of matrices encountered in statistics, such as projection matrices and positive definite matrices, and describes the special properties of those matrices. Finally, it covers numerical linear algebra, beginning with a discussion of the basics of numerical computations, and following up with accurate and efficient algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors.

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