Bayesian Information Criterion (BIC) for various fitting models of the centrality CCFCs.

kc is calculate from with xmin the the lower bound of the range of possible values that the random variable can attain. BIC is defined as k ln n − 2 ln L with k being the number of parameters estimated by the model, n number of data points in x, x the observed data and L the maximised value of the likelihood function of the model. The Model with the lowest BIC is preferred.