A COMPARISON OF METHODS FOR CONSTRUCTING CONFIDENCE SETS OF PHYLOGENETIC TREES USING MAXIMUM LIKELIHOOD
This thesis compares six phylogenetic tests, or equivalently, methods for con- structing confidence sets of phylogenetic trees : the Kishino-Hasegawa (KH) test statistic, Shimodaira–Hasegawa (SH), two versions of the Approximately Unbiased (AU) test, Chi-square and Bonferroni. The Bonferroni test is a new variation of the Chi-square test that corrects for selection bias. A variation of the AU test, AU Corrected, is considered that adjusts for difficulties arising when bootstrap support for trees is low. Confidence regions for each test are ex- amined using simulations from six and eight-taxon trees. We consider differing internal edge-lengths and challenging inference scenarios where some internal edge-lengths are equal to 0. In the second part of this thesis we apply the same tests to multiple real-world data sets, some with larger numbers of taxa, and make references to the observations and trends obtained in the previous part.