Maximum Likelihood Estimation of Symmetric Group-Based Models via Numerical Algebraic Geometry
Research output: Contribution to journal › Article › Scientific › peer-review
- University of Glasgow
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.
|Journal||Bulletin of Mathematical Biology|
|Publication status||Published - Feb 2019|
|MoE publication type||A1 Journal article-refereed|
- Algebraic statistics, Group-based models, Maximum likelihood estimation, Numerical algebraic geometry, Phylogenetics, Real algebraic geometry