Three statistical methods for sex determination in extant and fossil caprines: assessment of the Rupicapra long bones

Sex determination of fossil remains in archeopaleontological contexts is a necessary step in order to gain insights in archaeological and paleobiological parameters such as prey selection and sexual dimorphism. Species with higher sexual dimorphism are more reliably sexed while the sex determination of less dimorphic animals is not attempted. In this study, we compared the accuracy of three different methods in the sex determination of a modern known-sex sample of chamois (Rupicapra pyrenaica parva) from the Cantabrian range (Northern Iberian Peninsula), which is a small-sized ungulate with low sexual dimorphism when compared to other animals in which sex determination has been attempted (i.e., Ursus spelaeus, Capra pyrenaica). The three methods applied were mixture analysis (MA), cluster analysis (CA) and principal component analysis (PCA). Within CA we applied three different analysis: one agglomerative hierarchical method (AH) and two optimal partitioning methods (k-means and robust k-means); and within PCA we applied normal and robust variants of the analysis.