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Analyzing Large Data Sets in Reasonable Times: Solutions for Composite Optima
Article first published online: 19 JUL 2005
DOI: 10.1111/j.1096-0031.1999.tb00278.x
1096-0031/asset/cover.gif?v=1&s=a1d1ac4b2a76322ab60291f660f5ae12cde80e14 "Cladistics")
Additional Information
How to Cite
Goloboff, P. A. (1999), Analyzing Large Data Sets in Reasonable Times: Solutions for Composite Optima. Cladistics, 15: 415–428. doi: 10.1111/j.1096-0031.1999.tb00278.x
Publication History
- Issue published online: 19 JUL 2005
- Article first published online: 19 JUL 2005
- Accepted October 28, 1999
- Abstract
- References
- Cited By
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).