title: Random partition models and exchangeability for Bayesian identification of population structure.
abstract: We introduce a Bayesian theoretical formulation of the statistical learning problem concerning the genetic structure of populations. The two key concepts in our derivation are exchangeability in its various forms and random allocation models. Implications of our results to empirical investigation of the population structure are discussed.
authors.affiliation: Department of Mathematics and Statistics, Rolf Nevanlinna Institute, University of Helsinki, PO Box 68, Helsinki, FIN-00014, Finland. jukka.corander@helsinki.fi
authors.forename: Jukka
authors.initials: J
authors.lastname: Corander
authors.forename: Mats
authors.initials: M
authors.lastname: Gyllenberg
authors.forename: Timo
authors.initials: T
authors.lastname: Koski
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D005075:Biological Evolution; D004331:Drosophila melanogaster / Q000235:genetics; D005828:Genetics, Population; D008957:Models, Genetic