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An Analysis of Hominin Cranial Capacity Data Using Simulations

Darshi Arachige

The hominin cranial capacity data was reanalyzed using simulations, which emulated the variability in the estimation of cranial capacity of hominin skulls. First, the data was explored using k-means clustering to establish the presence of two groups in the data. The groups were further confirmed by using Hamming distance on the simulated cluster outcomes. Then, the resulting two datasets arising from two groups were used to estimate the confidence limits for the parameter estimates of Henneberg’s double exponential model. Through these parameter estimates and their confidence limits it could be seen that two models for two time spans identified by cluster analysis were better than a single model for the full span of time, which the previous authors considered to be the best option. From an analytical perspective, there are indications for a structural change in cranial capacity growth, which is expressed as a rapid increase after a slow growth period. This structural change scenario does not support the rejection of the concept of punctuated equilibrium on the basis of a gradual change based on the double exponential model.