Maximum Likelihood Estimation of Symmetric Group-Based Models via Numerical Algebraic Geometry

Research output: Contribution to journalArticleScientificpeer-review

Researchers

Research units

  • University of Glasgow

Abstract

Phylogenetic models admit polynomial parametrization maps in terms of the root distribution and transition probabilities along the edges of the phylogenetic tree. For symmetric continuous-time group-based models, Matsen studied the polynomial inequalities that characterize the joint probabilities in the image of these parametrizations (Matsen in IEEE/ACM Trans Comput Biol Bioinform 6:89–95, 2009). We employ this description for maximum likelihood estimation via numerical algebraic geometry. In particular, we explore an example where the maximum likelihood estimate does not exist, which would be difficult to discover without using algebraic methods.

Details

Original languageEnglish
Pages (from-to)337–360
JournalBulletin of Mathematical Biology
Volume81
Issue number2
Publication statusPublished - Feb 2019
MoE publication typeA1 Journal article-refereed

    Research areas

  • Algebraic statistics, Group-based models, Maximum likelihood estimation, Numerical algebraic geometry, Phylogenetics, Real algebraic geometry

Download statistics

No data available

ID: 29745741