期刊
BULLETIN OF MATHEMATICAL BIOLOGY
卷 69, 期 3, 页码 797-815出版社
SPRINGER
DOI: 10.1007/s11538-006-9161-1
关键词
Bayesian inference; genetic population structure; statistical learning theory
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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