Home
This Title All WIREs
WIREs RSS Feed
How to cite this WIREs title:
WIREs Comp Stat

Procrustes methods

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract The basic Procrustes problem is to transform a matrix to in order to match a target matrix . Matching necessitates that and have the same number of rows identified with the same entities but the columns are unrestricted in type and number. Special cases discussed are when T is an orthogonal, projection, or direction‐cosine matrix. Sometimes, both matrices are transformed and size parameters referring to isotropic and various forms of anisotropic scaling may be incorporated. Procrustes methods may be generalized to cover K transformed matrices , in which case their average (the group average) is important. Applications are in shape analysis, image analysis, psychometrics etc. Copyright © 2010 John Wiley & Sons, Inc. This article is categorized under: Statistical and Graphical Methods of Data Analysis > Multivariate Analysis Statistical and Graphical Methods of Data Analysis > Dimension Reduction

Browse by Topic

Statistical and Graphical Methods of Data Analysis > Dimensional Reduction
Statistical and Graphical Methods of Data Analysis > Multivariate Analysis

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts