:: Volume 13, Issue 1 (9-2019) ::
J. of Stat. Sci. 2019, 13(1): 185-196 Back to browse issues page
Regression Modelling of Shape Through Triangulation
Meysam Moghimbeygi, Mousa Golalizadeh *
Abstract:   (3514 Views)

Recalling the definition of shape as a point on hyper-sphere, proposed by Kendall, the regression model is studied in this paper. In order to simplify the modeling, the triangulation via two landmarks is proposed. The triangulation not only simplifies the regression modelling of the shapes but also provides straightforward computation procedure to reconstruct geometrical structure of the objects. Novelty of the proposed method in this paper is on using the predictor variable, based upon the shape, which suitably describes the geometrical variability of the response. The comparison and evaluation of the proposed methods with the full Procrustes matching through the mean square error criteria are done. Application of two models for the configurations of rat skulls is investigated.

Keywords: Pherical Regression, Shape Analysis, Triangulation, Procrustes Matching, Non-Euclidean Space.
Full-Text [PDF 532 kb]   (680 Downloads)    
Type of Study: Applied | Subject: Statistical Inference
Received: 2016/03/9 | Accepted: 2017/04/1 | Published: 2019/02/25

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Volume 13, Issue 1 (9-2019) Back to browse issues page