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Matrix algebra useful for statistics / Shayle R. Searle and Andrae I. Khuri.

By: Searle, Shayle R [author].
Contributor(s): Khuri, Andre I [author].
Material type: TextTextSeries: Wiley series in probability and statistics.Publisher: New Jersey : John Wiley & Sons, ©2017Edition: Second edition.Description: xxxi, 480 pages : illustrations ; 26 cm.ISBN: 9781118935149 (hbk).Subject(s): Matrices | Mathematical statisticsDDC classification: 512.9434
Contents:
1. Vector spaces, subspaces, and linear transformations -- 2. Matrix notation and terminology -- 3. Determinants -- 4. Matrix Operations -- 5. Special matrices -- 6. Eigenvalues and eigenvectors -- 7. Diagonalization of matrices -- 8. Generalized inverses -- 9. Matrix calculus -- 10. Multivariate distributions and quadratic forms -- 11. Matrix algebra of full-rank linear models -- 12. Less-than-full-rank linear models -- 13. Analysis of balanced linear models using direct products of matrices -- 14. Multiresponse models -- 15. SAS/IML -- 16. Use of MATLAB in matrix computations -- 17. Use of R in matrix computations.
Summary: This book addresses matrix algebra that is useful in the statistical analysis of data as well as within statistics as a whole. The material is presented in an explanatory style rather than a formal theorem-proof format and is self-contained. Featuring numerous applied illustrations, numerical examples, and exercises, the book has been updated to include the use of SAS, MATLAB, and R for the execution of matrix computations.
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Item type Current location Call number Status Date due Barcode Item holds
Books Books ISI Library, Kolkata
 
512.9434 Se439 (Browse shelf) Available 138274
Total holds: 0

Includes bibliographical references and index.

1. Vector spaces, subspaces, and linear transformations --
2. Matrix notation and terminology --
3. Determinants --
4. Matrix Operations --
5. Special matrices --
6. Eigenvalues and eigenvectors --
7. Diagonalization of matrices --
8. Generalized inverses --
9. Matrix calculus --
10. Multivariate distributions and quadratic forms --
11. Matrix algebra of full-rank linear models --
12. Less-than-full-rank linear models --
13. Analysis of balanced linear models using direct products of matrices --
14. Multiresponse models --
15. SAS/IML --
16. Use of MATLAB in matrix computations --
17. Use of R in matrix computations.

This book addresses matrix algebra that is useful in the statistical analysis of data as well as within statistics as a whole. The material is presented in an explanatory style rather than a formal theorem-proof format and is self-contained. Featuring numerous applied illustrations, numerical examples, and exercises, the book has been updated to include the use of SAS, MATLAB, and R for the execution of matrix computations.

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