Size and shape analysis of error-prone shape data

Du, J., Dryden, Ian L. and Huang, X. (2015) Size and shape analysis of error-prone shape data. Journal of the American Statistical Association, 110 (509). pp. 368-377. ISSN 1537-274X

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We consider the problem of comparing sizes and shapes of objects when landmark data are prone to measurement error. We show that naive implementation of ordinary Procrustes analysis that ignores measurement error can compromise inference. To account for measurement error, we propose the conditional score method for matching configurations, which guarantees consistent inference under mild model assumptions. The effects of measurement error on inference from naive Procrustes analysis and the performance of the proposed method are illustrated via simulation and application in three real data examples. Supplementary materials for this article are available online.

Item Type: Article
Keywords: Complex normal; Configuration; Landmark; Ordinary Procrustes analysis; Quaternion
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Mathematical Sciences
Identification Number:
Depositing User: Dryden, Professor Ian
Date Deposited: 07 Mar 2017 12:35
Last Modified: 04 May 2020 20:09

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