The Akaike Information Criterion (AIC) was then computed for each model: for normal errors and small sample sizes, AIC = 2* P + 2* P(P+1)/ N- P-1) + N*log (2π) + N*log (SSE/ N) + N where P is the number of estimated parameters (including the variance), N is the number of data points, and SSE is the sum of squared errors [ 2].
Because the number of data points N is small at 15, the small sample size corrected version of the AIC was used: AIC = 2* P + 2* P(P+1)/ N- P-1) + N*log (2π) + N*log (SSE/ N) + N where P is the number of estimated parameters (including the variance) and SSE is the sum of squared errors [ 24].
The full form of AICc is: {text{AICc}} = - 2left( {{ log } - {text{likelihood}}} right) + 2{text{K}} + frac{2K(K + 1)}{(n - K - 1)} (2 where K is the number of estimated parameters included in the model and n is the effective sample size.
Estimated parameters included the within-species pairwise diversity (Pi) at synonymous and non-synonymous sites, and the average number of nucleotide substitutions per site between species (Dxy).
Estimated parameters include a constant representing the mean rating; as well as variance estimates for the reviewer, patient record and review occasion for each of the four domains (hypertension, diabetes, COPD and acute care management).
Estimated parameters included fractional anisotropy (FA), a scalar ranging from 0 to 1, which quantifies the directional dependence of the diffusion signal and has been used as a measure of white matter integrity.
In such cases, not only is the parameter estimate shared among members of the group, but the uncertainty of the estimated parameter, including any bias that might be present, is also shared.
ABC is currently widely used to test scenarios and to estimate parameters including divergence time and population size in plants, animals and pathogens e.g. [ 5- 9].
To test for expansion in the Mediterranean, we used LAMARC 2.0 [ 46], which estimates parameters including population growth rate using coalescent theory and Metropolis Monte Carlo sampling technique.
Estimated parameters also included total amino acid differences (Na), uncorrected amino acid distances (p(aa)), poisson-corrected amino acid distances (D), number of synonymous substitutions per synonymous site (Ks) and number of nonsynonymous substitution per nonsynonymous site (Ka) [ 94].
We estimated several parameters, including width (w), center (c), delta (d, distance between the center and the tail), and tau (t, slope of the tail).
