Random partition models and exchangeability for Bayesian identification of population structure
Random partition models and exchangeability for Bayesian identification of population structure
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DOI：
10.1007/s11538-006-9161-1
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发表时间：
2007-04-01
影响因子：
3.5
通讯作者：
Koski, Timo
中科院分区：
文献类型：
--
作者：
Corander, Jukka;Gyllenberg, Mats;Koski, Timo
我们引入了有关群体遗传结构的统计学习问题的贝叶斯理论表述。我们推导中的两个关键概念是各种形式的可交换性和随机分配模型。讨论了我们的结果对人口结构实证研究的影响。
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.