the q-order partial correlation graph search algorithm, q-partial, or qp, algorithm for short, is a robust procedure for structure learning of undirected Gaussian graphical Markov models from "small n, large p" data, that is, multivariate normal data coming from a number of random variables p larger than the number of multidimensional data points n as in the case of, e.g., microarray data.
| Version: | 0.2-1 |
| Depends: | R (≥ 2.2.1) |
| Date: | 2006-12-18 |
| Author: | Robert Castelo, Alberto Roverato |
| Maintainer: | Robert Castelo <robert.castelo at upf.edu> |
| License: | GPL version 2 or newer |
| In views: | gR |
| CRAN checks: | qp results |
Downloads:
| Package source: | qp_0.2-1.tar.gz |
| MacOS X binary: | qp_0.2-1.tgz |
| Windows binary: | qp_0.2-1.zip |
| Reference manual: | qp.pdf |
| Old sources: | qp archive |