Learning Genetic Population Structures Using Minimization of Stochastic Complexity

Learning Genetic Population Structures Using Minimization of Stochastic Complexity

Considerable research efforts have been devoted to probabilistic modeling of genetic population structures within the past decade. In particular, a wide spectrum of Bayesian models have been proposed for unlinked molecular marker data from diploid organisms. Here we derive a theoretical framework fo...

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Bibliographic Details
Main Authors: Jukka Corander, Mats Gyllenberg, Timo Koski
Format: Article
Language:English
Published: MDPI AG 2010-05-01
Series:Entropy
Subjects:
factorization of multivariate distributions
finite mixture models
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population genetics
statistical learning
structured population
Online Access:http://www.mdpi.com/1099-4300/12/5/1102/

Internet

http://www.mdpi.com/1099-4300/12/5/1102/

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