Discriminant analysis and statistical pattern recognition. (Wiley series in probability and mathematical statistics; Applied probability and statistics). Ex-Library.

McLachlan, Geoffrey J.

ISBN 10: 0471615315 / ISBN 13: 9780471615316

Edité par John Wiley & Sons, Inc., New York, &c., 1992

A propos de cet article

xv, 526 p. N° de réf. du vendeur GU2409

Détails bibliographiques

Titre : Discriminant analysis and statistical ...

Éditeur : John Wiley & Sons, Inc., New York, &c.

Date d'édition : 1992

Reliure : Hardcover

Etat : Good

Etat de la jaquette : No dust jacket

A propos de ce titre

Synopsis :

This study is a systematic account of the subject area, concentrating on recent advances in the field. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule, and extensions of discriminant analysis motivated by problems in statistical image analysis. The accompanying bibliography contains over 1200 references.

Présentation de l'éditeur:

The Wiley–Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.

"For both applied and theoretical statisticians as well as investigators working in the many areas in which relevant use can be made of discriminant techniques, this monograph provides a modern, comprehensive, and systematic account of discriminant analysis, with the focus on the more recent advances in the field."
SciTech Book News

". . . a very useful source of information for any researcher working in discriminant analysis and pattern recognition."
Computational Statistics

Discriminant Analysis and Statistical Pattern Recognition provides a systematic account of the subject. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are regularized discriminant analysis and bootstrap–based assessment of the performance of a sample–based discriminant rule, and extensions of discriminant analysis motivated by problems in statistical image analysis. The accompanying bibliography contains over 1,200 references.