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Building mixture trees from binary sequence data

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  • Shu-Chuan Chen
  • Bruce G. Lindsay

Abstract

We develop a new method for building a hierarchical tree from binary sequence data. It is based on an ancestral mixture model. The sieve parameter in the model plays the role of time in the evolutionary tree of the sequences. By varying the sieve parameter, one can create a hierarchical tree that estimates the population structure at each fixed backward point in time. Application to the clustering of the mitochondrial DNA sequences of Griffiths & Tavare (1994) shows that the approach performs well. Theoretical and computational properties of the ancestral mixture model are further developed. Copyright 2006, Oxford University Press.

Suggested Citation

  • Shu-Chuan Chen & Bruce G. Lindsay, 2006. "Building mixture trees from binary sequence data," Biometrika, Biometrika Trust, vol. 93(4), pages 843-860, December.
    • Handle: RePEc:oup:biomet:v:93:y:2006:i:4:p:843-860
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    File URL: http://hdl.handle.net/10.1093/biomet/93.4.843
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    Cited by:

    1. Chen, Shu-Chuan (Grace) & Lindsay, Bruce, 2014. "Improving mixture tree construction using better EM algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 17-25.

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