The Open UniversitySkip to content
 

The orthogonally constrained regression revisited

Chu, M.T. and Trendafilov, N.T. (2001). The orthogonally constrained regression revisited. Journal of Computational and Graphical Statistics, 10(4) pp. 746–771.

URL: http://www.ingentaconnect.com/content/asa/jcgs/200...
DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1198/106186001317243430
Google Scholar: Look up in Google Scholar

Abstract

The Penrose regression problem, including the orthonormal Procrustes problem and rotation problemto a partially specified target, is an important class of data matching problems arising frequently in multivariate analysis, yet its optimality conditions have never been clearly understood.This work offers a way to calculate the projected gradient and the projectedHessian explicitly.One consequenceof this calculationis the complete characterization of the first order and the second order necessaryand sufficient optimality conditions for this problem. Another application is the natural formulation of a continuous steepest descent ow that can serve as a globally convergentnumerical method. Applications to the
orthonormal Procrustes problem and Penrose regression problem with partially specified target are demonstrated in this article. Finally, some numerical results are reported and commented.

Item Type: Journal Article
ISSN: 1061-8600
Keywords: Continuous-timeapproach; Penrose regression; Procrustes rotation; Rotation to partially specified target; Projected gradient; Projected Hessian; Optimality conditions.
Academic Unit/Department: Mathematics, Computing and Technology > Mathematics and Statistics
Item ID: 3959
Depositing User: Nickolay Trendafilov
Date Deposited: 04 Jul 2006
Last Modified: 02 Dec 2010 19:50
URI: http://oro.open.ac.uk/id/eprint/3959
Share this page:

Altmetrics

Scopus Citations

Actions (login may be required)

View Item
Report issue / request change

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340   general-enquiries@open.ac.uk