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This code provides a method to fit the hidden compact representation model as well as to identify the causal direction on discrete data. We implement an effective solution to recover the above hidden compact representation under the likelihood framework. Please see the Causal Discovery from Discrete Data using Hidden Compact Representation from NIPS 2018 by Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang and Zhifeng Hao (2018) <https://nips.cc/Conferences/2018/Schedule?showEvent=11274> for a description of some of our methods.
Version: | 0.1.1 |
Imports: | data.table (≥ 1.10.4), methods |
Published: | 2018-10-26 |
DOI: | 10.32614/CRAN.package.HCR |
Author: | Jie Qiao [aut, cre], Ruichu Cai [ths, aut], Kun Zhang [ths, aut], Zhenjie Zhang [ths, aut], Zhifeng Hao [ths, aut] |
Maintainer: | Jie Qiao <qiaojie.chn at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
Citation: | HCR citation info |
Materials: | README NEWS |
CRAN checks: | HCR results |
Reference manual: | HCR.pdf |
Package source: | HCR_0.1.1.tar.gz |
Windows binaries: | r-devel: HCR_0.1.1.zip, r-release: HCR_0.1.1.zip, r-oldrel: HCR_0.1.1.zip |
macOS binaries: | r-release (arm64): HCR_0.1.1.tgz, r-oldrel (arm64): HCR_0.1.1.tgz, r-release (x86_64): HCR_0.1.1.tgz, r-oldrel (x86_64): HCR_0.1.1.tgz |
Old sources: | HCR archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.