Matrix Algebra Useful for Statistics, 2e
Shayle R. Searle, Cornell University;
André I. Khuri, University of Florida
John Wiley & Sons, Inc., 2017
ISBN: 978-1-118-93514-9;
Language: English
Matrix Algebra Useful for Statistics 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 MATLAB for the execution of matrix computations. André I. Khuri, who has extensive research and teaching experience in the field, joins this edition as co-author. This is a textbook for advanced undergraduate and first-year graduate level courses in statistics and other related disciplines. The book is also appropriate as a reference for independent readers who use statistics and wish to improve their knowledge of matrix algebra.
The second edition also:
- Contains new coverage on vector spaces and linear transformations and discusses computational aspects of matrices
- Covers the analysis of balanced linear models using direct products of matrices
- Analyzes multiresponse linear models where several responses can be of interest
- Contains more than 400 examples and exercises to reinforce understanding, along with select solutions
- Includes plentiful new illustrations depicting the importance of geometry as well as historical interludes
MATLAB is primarily used in Chapter 16, which goes into detail on the use of MATLAB in matrix computations.
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