Linear algebra and matrix analysis for statistics /
Sudipto Banerjee, Professor of Biostatistics, School of Public Health, University of Minnesota, U.S.A., Anindya Roy, Professor of Statistics, Department of Mathematics and Statistics, University of Maryland, Baltimore County, U.S.A.
- 1st ed.
- Boca Raton : CRC Press, Taylor & Francis Group, 2014.
- xvii, 565 pages : illustrations ; 25 cm.
- Chapman & Hall/CRC texts in statistical science series .
Includes bibliographical references (pages 555-557) and 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."--