  The purpose of this article is to look at how information criteria, such as
AIC and BIC, relate to the g%SD fit criterion derived in Waddell et al. (2007,
2010a). The g%SD criterion measures the fit of data to model based on a
normalized weighted root mean square percentage deviation between the observed
data and model estimates of the data, with g%SD = 0 being a perfectly fitting
model. However, this criterion may not be adjusting for the number of
parameters in the model comprehensively. Thus, its relationship to more
traditional measures for maximizing useful information in a model, including
AIC and BIC, are examined. This results in an extended set of fit criteria
including g%AIC and g%BIC. Further, a broader range of asymptotically most
powerful fit criteria of the power divergence family, which includes maximum
likelihood (or minimum G^2) and minimum X^2 modeling as special cases, are used
to replace the sum of squares fit criterion within the g%SD criterion. Results
are illustrated with a set of genetic distances looking particularly at a range
of Jewish populations, plus a genomic data set that looks at how Neanderthals
and Denisovans are related to each other and modern humans. Evidence that Homo
erectus may have left a significant fraction of its genome within the Denisovan
is shown to persist with the new modeling criteria.
