Using the quantitative genetic threshold model for inferences between and within species.
Sewall Wright's threshold model has been used in modelling discrete traits that may have a continuous trait underlying them, but it has proven difficult to make efficient statistical inferences with it. The availability of Markov chain Monte Carlo (MCMC) methods makes possible likelihood and Bayesian inference using this model. This paper discusses prospects for the use of the threshold model in morphological systematics to model the evolution of discrete all-or-none traits. There the threshold model has the advantage over 0/1 Markov process models in that it not only accommodates polymorphism within species, but can also allow for correlated evolution of traits with far fewer parameters that need to be inferred. The MCMC importance sampling methods needed to evaluate likelihood ratios for the threshold model are introduced and described in some detail.
Felsenstein
Joseph
J
Department of Genome Sciences, University of Washington, Box 357730, Seattle, WA 98195-7730, USA. joe@gs.washington.edu
D001499:Bayes Theorem; D005075:Biological Evolution; D002965:Classification / Q000379:methods*; D016013:Likelihood Functions; D008390:Markov Chains; D008957:Models, Genetic; D009010:Monte Carlo Method; D010802:Phylogeny; D040641:Quantitative Trait Loci; D013045:Species Specificity