
handle: 2066/175035
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 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.
retinography, Procrustes analysis, Radboudumc 12: Sensory disorders DCMN: Donders Center for Medical Neuroscience, parabola fitting, Medical Imaging - Radboud University Medical Center, Estadística, robustez, parabolas retinografías, robustness, Computational methods for problems pertaining to statistics, Computing methodologies for image processing
retinography, Procrustes analysis, Radboudumc 12: Sensory disorders DCMN: Donders Center for Medical Neuroscience, parabola fitting, Medical Imaging - Radboud University Medical Center, Estadística, robustez, parabolas retinografías, robustness, Computational methods for problems pertaining to statistics, Computing methodologies for image processing
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