| Literature DB >> 16048785 |
Abstract
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.Mesh:
Year: 2005 PMID: 16048785 PMCID: PMC1569509 DOI: 10.1098/rstb.2005.1669
Source DB: PubMed Journal: Philos Trans R Soc Lond B Biol Sci ISSN: 0962-8436 Impact factor: 6.237