Matrix algebra useful for statistics / Shayle R. Searle and Andrae I. Khuri.
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TextSeries: Wiley series in probability and statisticsPublication details: New Jersey : John Wiley & Sons, ©2017.Edition: Second editionDescription: xxxi, 480 pages : illustrations ; 26 cmISBN: - 9781118935149 (hbk)
- 512.9434 23 Se439
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 512.9434 Se439 (Browse shelf(Opens below)) | Available | 138274 |
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| 512.9434 Sch415 Introduction to linear algebra and theory of matrices | 512.9434 Se439 Matrix algebra useful for statistics | 512.9434 Se439 Matrix algebra for the biological sciences ( including applications in statistics ) | 512.9434 Se439 Matrix algebra useful for statistics / | 512.9434 Se439s Matrix algebra useful for statistics | 512.9434 Se443 Matrix handbook for statisticians | 512.9434 Se474 Limiting spectral distribution of some patterned random matrices with independent entries/ |
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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