Journal
BULLETIN OF MATHEMATICAL BIOLOGY
Volume 69, Issue 3, Pages 797-815Publisher
SPRINGER
DOI: 10.1007/s11538-006-9161-1
Keywords
Bayesian inference; genetic population structure; statistical learning theory
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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.
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