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A Spatial Dirichlet Process Mixture Model for Clustering Population Genetics Data

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  • Brian J. Reich
  • Howard D. Bondell

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  • Brian J. Reich & Howard D. Bondell, 2011. "A Spatial Dirichlet Process Mixture Model for Clustering Population Genetics Data," Biometrics, The International Biometric Society, vol. 67(2), pages 381-390, June.
    • Handle: RePEc:bla:biomet:v:67:y:2011:i:2:p:381-390
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2010.01484.x
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    References listed on IDEAS

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    1. Jukka Corander & Jukka Sirén & Elja Arjas, 2008. "Bayesian spatial modeling of genetic population structure," Computational Statistics, Springer, vol. 23(1), pages 111-129, January.
    2. Sinae Kim & Mahlet G. Tadesse & Marina Vannucci, 2006. "Variable selection in clustering via Dirichlet process mixture models," Biometrika, Biometrika Trust, vol. 93(4), pages 877-893, December.
    3. Sijian Wang & Ji Zhu, 2008. "Variable Selection for Model-Based High-Dimensional Clustering and Its Application to Microarray Data," Biometrics, The International Biometric Society, vol. 64(2), pages 440-448, June.
    4. Dahl, David B. & Newton, Michael A., 2007. "Multiple Hypothesis Testing by Clustering Treatment Effects," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 517-526, June.
    5. Tadesse, Mahlet G. & Sha, Naijun & Vannucci, Marina, 2005. "Bayesian Variable Selection in Clustering High-Dimensional Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 602-617, June.
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