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) <arXiv:1403.2310>.
| Version: | 0.0.7 |
| Depends: | R (≥ 3.2.3) |
| Imports: | Rcpp (≥ 0.11.0), sparsebnUtils (≥ 0.0.4), igraph |
| LinkingTo: | Rcpp, RcppEigen |
| Suggests: | testthat |
| Published: | 2020-03-12 |
| 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_0.0.7.tar.gz |
| Windows binaries: | r-devel: discretecdAlgorithm_0.0.7.zip, r-release: discretecdAlgorithm_0.0.7.zip, r-oldrel: discretecdAlgorithm_0.0.7.zip |
| macOS binaries: | r-release (arm64): discretecdAlgorithm_0.0.7.tgz, r-oldrel (arm64): discretecdAlgorithm_0.0.7.tgz, r-release (x86_64): discretecdAlgorithm_0.0.7.tgz, r-oldrel (x86_64): discretecdAlgorithm_0.0.7.tgz |
| Old sources: | discretecdAlgorithm archive |
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