title: Statistics of the log-det estimator.
abstract: The log-det estimator is a measure of divergence (evolutionary distance) between sequences of biological characters, DNA or amino acids, for example, and has been shown to be robust to biases in composition that can cause problems for other estimators. We provide a statistical framework to construct high-accuracy confidence intervals for log-det estimates and compare the efficiency of the estimator to that of maximum likelihood using time-reversible Markov models. The log-det estimator is found to have good statistical properties under such general models.
authors: European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, UK. tim.massingham@ebi.ac.uk
authors: T
authors: T
authors: Massingham
authors: N
authors: N
authors: Goldman
mesh_terms: D000818:Animals; D001483:Base Sequence; D004272:DNA, Mitochondrial / Q000032:analysis; D049810:Genetic Speciation; D006801:Humans; D016013:Likelihood Functions; D008390:Markov Chains; D008433:Mathematics; D008957:Models, Genetic; D015233:Models, Statistical; D008969:Molecular Sequence Data; D011148:Pongo pygmaeus / Q000235:genetics; D017422:Sequence Analysis, DNA
chemical_list: D004272:DNA, Mitochondrial