Package: copent 0.5
copent: Estimating Copula Entropy and Transfer Entropy
The nonparametric methods for estimating copula entropy, transfer entropy, and the statistics for multivariate normality test and two-sample test are implemented. The methods for estimating transfer entropy and the statistics for multivariate normality test and two-sample test are based on the method for estimating copula entropy. The method for change point detection with copula entropy based two-sample test is also implemented. Please refer to Ma and Sun (2011) <doi:10.1016/S1007-0214(11)70008-6>, Ma (2019) <doi:10.48550/arXiv.1910.04375>, Ma (2022) <doi:10.48550/arXiv.2206.05956>, Ma (2023) <doi:10.48550/arXiv.2307.07247>, and Ma (2024) <doi:10.48550/arXiv.2403.07892> for more information.
Authors:
copent_0.5.tar.gz
copent_0.5.zip(r-4.7)copent_0.5.zip(r-4.6)copent_0.5.zip(r-4.5)
copent_0.5.tgz(r-4.6-any)copent_0.5.tgz(r-4.5-any)
copent_0.5.tar.gz(r-4.7-any)copent_0.5.tar.gz(r-4.6-any)
copent_0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
copent/json (API)
| # Install 'copent' in R: |
| install.packages('copent', repos = c('https://majianthu.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/majianthu/copent/issues
causal-discoverycausalitychange-point-detectionconditional-independence-testconditional-mutual-informationcopulacopula-entropycorrelationentropygranger-causalityinformation-theorymutual-informationmutualinfnormality-testtransfer-entropytwo-sample-testvariable-selection
Last updated from:1ddf260860. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 100 | ||
| source / vignettes | OK | 138 | ||
| linux-release-x86_64 | OK | 113 | ||
| macos-release-arm64 | OK | 171 | ||
| macos-oldrel-arm64 | OK | 166 | ||
| windows-devel | OK | 72 | ||
| windows-release | OK | 74 | ||
| windows-oldrel | OK | 63 | ||
| wasm-release | OK | 81 |
Exports:ciconstruct_empirical_copulacopentcpdentknnmcpdmvnttransenttst
Dependencies:
