Quantitative Sex Estimation Based on Cranial Traits Using R Functions

Abstract

This paper presents an R script that quantifies the shape of selected cranial traits and automates sex estimation. The proposed functions were tested on two modern Greek assemblages. The discriminant variables input in the functions are calculated from a digital photograph of the lateral view of the cranium. The cranial outline is determined using the Canny edge detector and discriminant variables that quantify the shape of the glabella/frontal bone, mastoid process, and external occipital protuberance are computed. The best cross-validated results for pooled sexes in the Athens Collection range from 84.2% to 87.3%, and increase up to 93.9% when half of the sample is used for training and the rest for prediction, while correct classification for the Cretan material is 80–90% for optimum combinations of discriminant variables. The greatest advantage of the proposed method is its straightforward and time-efficient application.