Analyzing Large Data Sets in Reasonable Times: Solutions for Composite Optima

Authors

  • Pablo A. Goloboff

    1. Consejo Nacional de Investigaciones Cientificas y Técnicas, Instituto Miguel Lillo, Miguel Lillo 205, 4000 S. M. de Tucumn, Argentina
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Abstract

New methods for parsimony analysis of large data sets are presented. The new methods are sectorial searches, tree-drifting, and tree-fusing. For Chase et al.'s 500-taxon data set these methods (on a 266-MHz Pentium II) find a shortest tree in less than 10 min (i.e., over 15,000 times faster than PAUP and 1000 times faster than PAUP*). Making a complete parsimony analysis requires hitting minimum length several times independently, but not necessarily all “islands” for Chase et al.'s data set, this can be done in 4 to 6 h. The new methods also perform well in other cases analyzed (which range from 170 to 854 taxa).

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