Robust Morphometric Analysis based on Landmarks. Applications

Procrustes Analysis is a Morphometric method based on Configurations of Landmarks that estimates the superimposition parameters by least-squares; for this reason, the procedure is very sensitive to outliers. In the first part of the paper we robustify this technique to classify individuals from a descriptive point of view. In the literature there are also classical results, based on the normality of the observations, to test whether there are significant differences between individuals. In the second part of the paper we determine a Von Mises plus Saddlepoint approximation for the tail probability of the Procrustes Statistic when the observations come from a model close to the normal. We conclude the paper with some applications using the Geographical Information System QGIS.