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An extended model for phylogenetic maximum likelihood based on discrete morphological characters

Author

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  • Spade David A.

    (University of Wisconsin Milwaukee, Mathematical Sciences, EMS Building Room 403, 3200 Cramer Street, Milwaukee, WI, USA)

Abstract

Maximum likelihood is a common method of estimating a phylogenetic tree based on a set of genetic data. However, models of evolution for certain types of genetic data are highly flawed in their specification, and this misspecification can have an adverse impact on phylogenetic inference. Our attention here is focused on extending an existing class of models for estimating phylogenetic trees from discrete morphological characters. The main advance of this work is a model that allows unequal equilibrium frequencies in the estimation of phylogenetic trees from discrete morphological character data using likelihood methods. Possible extensions of the proposed model will also be discussed.

Suggested Citation

  • Spade David A., 2020. "An extended model for phylogenetic maximum likelihood based on discrete morphological characters," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 19(1), pages 1-11, February.
    • Handle: RePEc:bpj:sagmbi:v:19:y:2020:i:1:p:11:n:2
    DOI: 10.1515/sagmb-2019-0029
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    References listed on IDEAS

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    1. Matthew Stephens & Peter Donnelly, 2000. "Inference in molecular population genetics," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 605-635.
    2. April M Wright & David M Hillis, 2014. "Bayesian Analysis Using a Simple Likelihood Model Outperforms Parsimony for Estimation of Phylogeny from Discrete Morphological Data," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-6, October.
    3. Bob Mau & Michael A. Newton & Bret Larget, 1999. "Bayesian Phylogenetic Inference via Markov Chain Monte Carlo Methods," Biometrics, The International Biometric Society, vol. 55(1), pages 1-12, March.
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