{2}-Inverses and Their Statistical Application

Albert J. Getson

ISBN 10: 0387968490 / ISBN 13: 9780387968490

Verlag: Springer, Springer, 1988

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - Much of the traditional approach to linear model analysis is bound up in complex matrix expressions revolving about the usual generalized inverse. Motivated by this important role of the generalized inverse. the research summarized here began as an interest in understanding. in geometric terms. the four conditions defining the qnique Moore-Penrose Inverse. Such an investigation. it was hoped. might lead to a better understanding. and possibly a simplification of. the usual matrix expressions. Initially this research was begun by Francis Hsuan and Pat Langenberg, without knowledge of Kruskal's paper published in 1975. This oversight was perhaps fortu nate. since if they had read his paper they may not have continued their effort. A summary of this early research appears in Hsuan. Langenberg and Getson (1985). This monograph is a summary of the research on {2}-inverses continued by Al Getson. while a graduate student. in collaboration with Francis Hsuan of the Depart ment of Statistics. School of Business Administration. at Temple University. Philadelphia. The literature on generalized inverses and related topics is extensive and some of what is present here has appeared elsewhere. Generally. this literature is not presented from the point of view of {2}-inverses. We have tried to do justice to . the relevant published works and appologize for those we have either overlooked or possibly misrepresented.

Bestandsnummer des Verkäufers 9780387968490

Bibliografische Details

• Titel: {2}-Inverses and Their Statistical Application
• Verlag: Springer, Springer
• Erscheinungsjahr: 1988
• Sprache: Englisch
• ISBN-10: 0387968490
• ISBN-13: 9780387968490
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 244B x 170 H x 8 T Millimeter Breite: 244 mm, Höhe: 170 mm, Tiefe: 8 mm
• Gewicht: 229 Gramm

Über diesen Titel

Inhaltsangabe

A 2-inverse for a matrix A is any matrix G satisfying GAG=G. This book adresses the special, but heretofore ignored, role of 2-inverses in statistics. The relationship among various kinds of generalized inverses and their construction in terms of 2-inverses are explored. The applications discussed include the role of 2-inverses in: canonically representing second-degree polynomials x'Ax+b'x+c, obtaining vectors ß which satisfy K'ß=0 and minimize y'y-Xß(squared), and relating the hypotheses tested by various analytical approaches in generalized linear models. For each topic, the simplification of both the concepts and the notation which results from a 2-inverse approach is stressed and illustrated with examples.

Reseña del editor

Much of the traditional approach to linear model analysis is bound up in complex matrix expressions revolving about the usual generalized inverse. Motivated by this important role of the generalized inverse. the research summarized here began as an interest in understanding. in geometric terms. the four conditions defining the qnique Moore-Penrose Inverse. Such an investigation. it was hoped. might lead to a better understanding. and possibly a simplification of. the usual matrix expressions. Initially this research was begun by Francis Hsuan and Pat Langenberg, without knowledge of Kruskal's paper published in 1975. This oversight was perhaps fortu­ nate. since if they had read his paper they may not have continued their effort. A summary of this early research appears in Hsuan. Langenberg and Getson (1985). This monograph is a summary of the research on {2}-inverses continued by Al Getson. while a graduate student. in collaboration with Francis Hsuan of the Depart­ ment of Statistics. School of Business Administration. at Temple University. Philadelphia. The literature on generalized inverses and related topics is extensive and some of what is present here has appeared elsewhere. Generally. this literature is not presented from the point of view of {2}-inverses. We have tried to do justice to . the relevant published works and appologize for those we have either overlooked or possibly misrepresented.