Gruber Matrix Algebra for Linear Models

1. Auflage 2013
ISBN: 978-1-118-80041-6
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 224 Seiten, E-Book

A self-contained introduction to matrix analysis theory andapplications in the field of statistics
Comprehensive in scope, Matrix Algebra for Linear Modelsoffers a succinct summary of matrix theory and its relatedapplications to statistics, especially linear models. The bookprovides a unified presentation of the mathematical properties andstatistical applications of matrices in order to define andmanipulate data.
Written for theoretical and applied statisticians, the bookutilizes multiple numerical examples to illustrate key ideas,methods, and techniques crucial to understanding matrixalgebra's application in linear models. Matrix Algebra forLinear Models expertly balances concepts and methods allowingfor a side-by-side presentation of matrix theory and its linearmodel applications. Including concise summaries on each topic, thebook also features:
* Methods of deriving results from the properties of eigenvaluesand the singular value decomposition
* Solutions to matrix optimization problems for obtaining moreefficient biased estimators for parameters in linear regressionmodels
* A section on the generalized singular value decomposition
* Multiple chapter exercises with selected answers to enhanceunderstanding of the presented material
Matrix Algebra for Linear Models is an ideal textbook foradvanced undergraduate and graduate-level courses on statistics,matrices, and linear algebra. The book is also an excellentreference for statisticians, engineers, economists, and readersinterested in the linear statistical model.

Autoren/Hrsg.

Gruber, Marvin H. J.

Über Autor(innen)

Marvin H. J. Gruber, PHD, is Professor Emeritus in theSchool of Mathematical Sciences at Rochester Institute ofTechnology. He has authored several books and journal articles inhis areas of research interest, which include improving theefficiency of regression estimators. Dr. Gruber is a member of theAmerican Mathematical Society and the American StatisticalAssociation.