Determining the distribution of fitness effects using a generalized Beta-Burr distribution.

ABSTRACT

In Beisel et al. (2007), a likelihood framework, based on extreme value theory (EVT), was developed for determining the distribution of fitness effects for adaptive mutations. In this paper we extend this framework beyond the extreme distributions and develop a likelihood framework for testing whether or not extreme value theory applies. By making two simple adjustments to the Generalized Pareto Distribution (GPD) we introduce a new simple five parameter probability density function that incorporates nearly every common (continuous) probability model ever used. This means that all of the common models are nested. This has important implications in model selection beyond determining the distribution of fitness effects. However, we demonstrate the use of this distribution utilizing likelihood ratio testing to evaluate alternative distributions to the Gumbel and Weibull domains of attraction of fitness effects. We use a bootstrap strategy, utilizing importance sampling, to determine where in the parameter space will the test be most powerful in detecting deviations from these domains and at what sample size, with focus on small sample sizes (n<20). Our results indicate that the likelihood ratio test is most powerful in detecting deviation from the Gumbel domain when the shape parameters of the model are small while the test is more powerful in detecting deviations from the Weibull domain when these parameters are large. As expected, an increase in sample size improves the power of the test. This improvement is observed to occur quickly with sample size n≥10 in tests related to the Gumbel domain and n≥15 in the case of the Weibull domain. This manuscript is in tribute to the contributions of Dr. Paul Joyce to the areas of Population Genetics, Probability Theory and Mathematical Statistics. A Tribute section is provided at the end that includes Paul's original writing in the first iterations of this manuscript. The Introduction and Alternatives to the GPD sections were obtained from the last iteration that Paul and I have worked on, with some adjustments. I hope that the rest gives justice to his thoughts and possible conclusions that he might have wanted to portray.