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Support Weighting
Author(s) -
Farris James S.
Publication year - 2001
Publication title -
cladistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.323
H-Index - 92
eISSN - 1096-0031
pISSN - 0748-3007
DOI - 10.1111/j.1096-0031.2001.tb00133.x
Subject(s) - weighting , jackknife resampling , resampling , compatibility (geochemistry) , stability (learning theory) , mathematics , statistics , reliability (semiconductor) , computer science , machine learning , engineering , physics , power (physics) , quantum mechanics , estimator , chemical engineering , acoustics
Previous weighting methods—including compatibility weighting—have assumed that homoplasy indicates unreliability, but this assumption does not seem to hold for large molecular data matrices. Reliability can be better assessed by support weighting, which measures the degree to which the changes in a character (site) are concentrated in the supported branches of a tree. Jackknife resampling can be used to generate randomly selected suites of initial weights in successive support weighting, and this provides a way of assessing the stability of successive weighting results.