Package: HCR 0.1.1
HCR: Causal Discovery from Discrete Data using Hidden Compact Representation
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.
Authors:
HCR_0.1.1.tar.gz
HCR_0.1.1.zip(r-4.7-any)HCR_0.1.1.zip(r-4.6-any)HCR_0.1.1.zip(r-4.5-any)
HCR_0.1.1.tgz(r-4.6-any)HCR_0.1.1.tgz(r-4.5-any)
HCR_0.1.1.tar.gz(r-4.7-any)HCR_0.1.1.tar.gz(r-4.6-any)
HCR_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
HCR/json (API)
| # Install 'HCR' in R: |
| install.packages('HCR', repos = c('https://jie-qiao.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:827a42d1c3. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 87 | ||
| source / vignettes | OK | 129 | ||
| linux-release | OK | 84 | ||
| macos-release | OK | 135 | ||
| macos-oldrel | OK | 153 | ||
| windows-devel | OK | 58 | ||
| windows-release | OK | 60 | ||
| windows-oldrel | OK | 59 | ||
| wasm-release | OK | 86 |
Dependencies:data.table
