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Applied Probability Trust (1 February 2008) IDENTIFIABILITY OF A MARKOVIAN MODEL OF
 

Summary: Applied Probability Trust (1 February 2008)
IDENTIFIABILITY OF A MARKOVIAN MODEL OF
MOLECULAR EVOLUTION WITH GAMMA-DISTRIBUTED RATES
ELIZABETH S. ALLMAN,
University of Alaska Fairbanks
CŽECILE ANŽE,
University of Wisconsin Madison
JOHN A. RHODES,
University of Alaska Fairbanks
Abstract
Inference of evolutionary trees and rates from biological sequences is commonly
performed using continuous-time Markov models of character change. The
Markov process evolves along an unknown tree while observations arise only
from the tips of the tree. Rate heterogeneity is present in most real data sets
and is accounted for by the use of flexible mixture models where each site is
allowed its own rate. Very little has been rigorously established concerning
the identifiability of the models currently in common use in data analysis,
although non-identifiability was proven for a semi-parametric model and an
incorrect proof of identifiability was published for a general parametric model
(GTR++I). Here we prove that one of the most widely used models (GTR+)

  

Source: Allman, Elizabeth S. - Department of Mathematical Sciences, University of Alaska Fairbanks

 

Collections: Mathematics