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Random partition models and exchangeability for Bayesian identification of population structure
2007 (English)In: Bulletin of Mathematical Biology, ISSN 0092-8240, E-ISSN 1522-9602, Vol. 69, no 3, 797-815 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2007. Vol. 69, no 3, 797-815 p.
Keyword [en]
Bayesian inference, genetic population structure, statistical learning, theory, ewens sampling formula, set, sufficientness, inference, urns
Identifiers
URN: urn:nbn:se:kth:diva-16477DOI: 10.1007/s11538-006-9161-1ISI: 000245124600001OAI: oai:DiVA.org:kth-16477DiVA: diva2:334519
Note
QC 20100525Available from: 2010-08-05 Created: 2010-08-05 Last updated: 2017-12-12Bibliographically approved

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Koski, Timo

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