Structure learning of Bayesian network using coordinate-descent algorithm. This algorithm is designed for discrete network assuming a multinomial data set, and we use a multi-logit model to do the regression. The algorithm is described in Gu, Fu and Zhou (2016) <http://arxiv.org/abs/1403.2310>.
| Version: | 0.0.1 |
| Depends: | R (≥ 3.2.3) |
| Imports: | Rcpp, sparsebnUtils, nnet |
| LinkingTo: | Rcpp, RcppEigen |
| Suggests: | testthat |
| Published: | 2016-08-11 |
| Author: | Jiaying Gu [aut, cre] |
| Maintainer: | Jiaying Gu <gujy.lola at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| SystemRequirements: | C++11 |
| Materials: | README |
| CRAN checks: | discretecdAlgorithm results |
| Reference manual: | discretecdAlgorithm.pdf |
| Package source: | discretecdAlgorithm_0.0.1.tar.gz |
| Windows binaries: | r-devel: discretecdAlgorithm_0.0.1.zip, r-release: discretecdAlgorithm_0.0.1.zip, r-oldrel: discretecdAlgorithm_0.0.1.zip |
| OS X Mavericks binaries: | r-release: discretecdAlgorithm_0.0.1.tgz, r-oldrel: discretecdAlgorithm_0.0.1.tgz |
| Reverse depends: | sparsebn |
Please use the canonical form https://CRAN.R-project.org/package=discretecdAlgorithm to link to this page.