Procrustes Problems

John C. Gower, Garmt B. Dijksterhuis - Collection Oxford Statistical Science Series

233 pages, parution le 06/02/2004

Ajouter à une liste

Indisponible

Résumé

Procrustean methods are used to transform one set of data to represent another set of data as closely as possible. The name derives from the Greek myth where Procrustes invited passers-by in for a pleasant meal and a night's rest on a magical bed that would exactly fit any guest. He then either stretched the guest on the rack or cut off their legs to make them fit perfectly into the bed. Theseus turned the tables on Procrustes, fatally adjusting him to fit his own bed. The text is the first systematic overview of Procrustean methods in one volume, presenting a unifying Analysis of Variance framework for different matching methods and the development of statistical tests.

Readership: Statisticians, data analysts and research workers using Procrustean methods, graduate students of statistics and multivariate analysis, specialists in many other fields involved in analysing data

First systematic overview of Procrustean methods in one volume
Multi-disciplinary - these matching methods are used in many fields involving data analysis at research level
Contains new algorithms
Presents a unifying ANOVA framework

L'auteur - John C. Gower

Professor, Open University, Walton Hall, Statistics Department, Milton Keynes

L'auteur - Garmt B. Dijksterhuis

Senior Scientist, WUR Wageningen University and Research Centre, ATO Agrotechnological Institute, Sensory and Consumer Science Group, Wageningen, the Netherlands; Visiting Associate Research Professor, KVL, Royal Veterinary and Agricultural University, Department of Dairy and Food Science, Sensory Science Group, Copenhagen, Denmark

Sommaire

Introduction
Initial transformations
Two-set Procrustes problems: generalities
Orthogonal Procrustes problems
Projection Procrustes problems
Oblique Procrustes problems
Other two-sets Procrustes problems
Weighting, scaling and missing values
Generalised Procrustes problems
Analysis of variance framework
Incorporating information on variables
Accuracy and stability
Links with other methods
Some application areas, future and conclusion
Configurations
Rotations and reflections
Orthogonal projections
Oblique axes
A minimisation problem
Symmetric matrix products
References

Voir tout

Replier

Caractéristiques techniques

	PAPIER
Éditeur(s)	Oxford University Press
Auteur(s)	John C. Gower, Garmt B. Dijksterhuis
Collection	Oxford Statistical Science Series
Parution	06/02/2004
Nb. de pages	233
Format	16 x 24
Couverture	Relié
Poids	470g
Intérieur	Noir et Blanc
EAN13	9780198510581
ISBN13	978-0-19-851058-1