ESTIMATING CHARACTER WEIGHTS DURING TREE SEARCH

TLDR

The authors propose a non‑iterative method that weights characters by homoplasy without requiring separate weight estimation. The method searches for trees maximizing total fit, where each character’s fit is a concave function of its homoplasy, so that steps in highly homoplastic characters are down‑weighted and character reliability is inferred from the trees compared. The resulting fittest trees assign higher reliability to characters and reduce steps for those fitting the tree, while any alternative tree that saves steps in some characters must incur extra steps in less homoplastic ones.

Abstract

Abstract- A new method for weighting characters according to their homoplasy is proposed; the method is non-iterative and does not require independent estimations of weights. It is based on searching trees with maximum total fit, with character fits defined as a concave function of homoplasy. Then, when comparing trees, differences in steps occurring in characters which show more homoplasy on the trees are less influential. The reliability of the characters is estimated, during the analysis, as a logical implication of the trees being compared. The "fittest" trees imply that the characters are maximally reliable and, given character conflict, have fewer steps for the characters which fit the tree better. If other trees save steps in some characters, it will be at the expense of gaining them in characters with less homoplasy.