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Linear algebra and matrix analysis for statistics / Sudipto Banerjee, and Anindya Roy.

By: Contributor(s): Material type: TextTextSeries: Chapman & Hall/CRC texts in statistical science seriesPublication details: Boca Raton : CRC Press, 2014.Description: xvii, 565 p. ; 25 cmISBN:
  • 9781420095388 (hardback)
Subject(s): DDC classification:
  • 23 B215 512.5
Contents:
1. Matrices, vectors and their operations-- 2. Systems of linear equations-- 3. More on linear equations-- 4. Euclidean spaces-- 5. The rank of a matrix-- 6. Complementary subspaces-- 7. Orthogonality, orthogonal subspaces and projections-- 8. More on orthogonality-- 9. Revisiting linear equations-- 10. Determinants-- 11. Eigenvalues and eigenvectors-- 12. Singular value and Jordan decompositions-- 13. Quadratic forms-- 14. The Kronecker product and related operations-- 15. Linear iterative systems, norms and convergence-- 16. Abstract linear algebra-- References-- Index.
Summary: "Linear algebra and the study of matrix algorithms have become fundamental to the development of statistical models. Using a vector-space approach, this book provides an understanding of the major concepts that underlie linear algebra and matrix analysis. Each chapter introduces a key topic, such as infinite-dimensional spaces, and provides illustrative examples. The authors examine recent developments in diverse fields such as spatial statistics, machine learning, data mining, and social network analysis. Complete in its coverage and accessible to students without prior knowledge of linear algebra, the text also includes results that are useful for traditional statistical applications."--
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 512.5 B215 (Browse shelf(Opens below)) Available 135574
Books ISI Library, Kolkata 512.5 B215 (Browse shelf(Opens below)) Checked out 08/12/2024 C26272
Total holds: 0

Includes bibliographical references and index.

1. Matrices, vectors and their operations--
2. Systems of linear equations--
3. More on linear equations--
4. Euclidean spaces--
5. The rank of a matrix--
6. Complementary subspaces--
7. Orthogonality, orthogonal subspaces and projections--
8. More on orthogonality--
9. Revisiting linear equations--
10. Determinants--
11. Eigenvalues and eigenvectors--
12. Singular value and Jordan decompositions--
13. Quadratic forms--
14. The Kronecker product and related operations--
15. Linear iterative systems, norms and convergence--
16. Abstract linear algebra--

References--
Index.

"Linear algebra and the study of matrix algorithms have become fundamental to the development of statistical models. Using a vector-space approach, this book provides an understanding of the major concepts that underlie linear algebra and matrix analysis. Each chapter introduces a key topic, such as infinite-dimensional spaces, and provides illustrative examples. The authors examine recent developments in diverse fields such as spatial statistics, machine learning, data mining, and social network analysis. Complete in its coverage and accessible to students without prior knowledge of linear algebra, the text also includes results that are useful for traditional statistical applications."--

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