Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4949331 | Computational Statistics & Data Analysis | 2017 | 16 Pages |
Abstract
A novel approach to fitting parabolas to scattered data is introduced by putting special emphasis on the robustness of the approach. The robust fit is achieved by not taking into account a proportion α of the “most outlying” observations, allowing the procedure to trim them off. The most outlying observations are self-determined by the data. Procrustes analysis techniques and a particular type of “concentration” steps are the keystone of the proposed methodology. An application to a retinographic study is also presented.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Luis A. GarcÃa-Escudero, AgustÃn Mayo-Iscar, Clara I. Sánchez-Gutiérrez,