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Matrix Algebra

Theory, Computations, and Applications in Statistics
 Taschenbuch
Besorgungstitel | Lieferzeit:3-5 Tage I
ISBN-13:
9781441924247
Einband:
Taschenbuch
Seiten:
530
Autor:
James E. Gentle
Gewicht:
826 g
Format:
235x155x mm
Serie:
Springer Texts in Statistics
Sprache:
Englisch
Beschreibung:

This much-needed work presents, among other things, the relevant aspects of the theory of matrix algebra for applications in statistics. Written in an informal style, it addresses computational issues and places more emphasis on applications than existing texts.
Linear Algebra.- Basic Vector/Matrix Structure and Notation.- Vectors and Vector Spaces.- Basic Properties of Matrices.- Vector/Matrix Derivatives and Integrals.- Matrix Transformations and Factorizations.- Solution of Linear Systems.- Evaluation of Eigenvalues and Eigenvectors.- Applications in Data Analysis.- Special Matrices and Operations Useful in Modeling and Data Analysis.- Selected Applications in Statistics.- Numerical Methods and Software.- Numerical Methods.- Numerical Linear Algebra.- Software for Numerical Linear Algebra.
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.

This much-needed work presents, among other things, the relevant aspects of the theory of matrix algebra for applications in statistics. Written in an informal style, it addresses computational issues and places more emphasis on applications than existing texts.
Linear Algebra.- Basic Vector/Matrix Structure and Notation.- Vectors and Vector Spaces.- Basic Properties of Matrices.- Vector/Matrix Derivatives and Integrals.- Matrix Transformations and Factorizations.- Solution of Linear Systems.- Evaluation of Eigenvalues and Eigenvectors.- Applications in Data Analysis.- Special Matrices and Operations Useful in Modeling and Data Analysis.- Selected Applications in Statistics.- Numerical Methods and Software.- Numerical Methods.- Numerical Linear Algebra.- Software for Numerical Linear Algebra.
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.
Autor: James E. Gentle
ISBN-13:: 9781441924247
ISBN: 1441924248
Verlag: Springer, Berlin
Gewicht: 826g
Seiten: 530
Sprache: Englisch
Sonstiges: Taschenbuch, 235x155x mm