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Matrix algebra : theory, computations and applications in statistics / James E. Gentle.

By: Material type: TextTextSeries: Springer texts in statisticsPublication details: Cham : Springer, 2017.Edition: 2nd edDescription: xxix, 648 pages : illustrations ; 26 cmISBN:
  • 9783319648668
Subject(s): DDC classification:
  • 512.9434 23 G338
Contents:
Part I. Linear algebra. 1. Basic vector/matrix structure and notation -- 2. Vectors and vector spaces -- 3. Basic properties of matrices -- 4. Vector/matrix derivatives and integrals -- 5. Matrix transformations and factorizations -- 6. Solution of linear systems -- 7. Evaluation of eigenvalues and eigenvectors -- -- Part II. Applications in data analysis. 8. Special matrices and operations useful in modeling and data analysis -- 9. Selected applications in statistics -- -- Part III. Numerical methods and software. 10. Numerical methods -- 11. Numerical linear algebra -- 12. Software for numerical linear algebra -- Appendices and back matter. Notation and definitions -- Solutions and hints for selected exercises.
Summary: 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.
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Include indexes and bibliographical references and index.

Part I. Linear algebra.
1. Basic vector/matrix structure and notation --
2. Vectors and vector spaces --
3. Basic properties of matrices --
4. Vector/matrix derivatives and integrals --
5. Matrix transformations and factorizations --
6. Solution of linear systems --
7. Evaluation of eigenvalues and eigenvectors --
--
Part II. Applications in data analysis.
8. Special matrices and operations useful in modeling and data analysis --
9. Selected applications in statistics --
--
Part III. Numerical methods and software.
10. Numerical methods --
11. Numerical linear algebra --
12. Software for numerical linear algebra --
Appendices and back matter.
Notation and definitions --
Solutions and hints for selected exercises.

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.

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