semidist: Measure Dependence Between Categorical and Continuous Variables
Semi-distance and mean-variance (MV) index are proposed to measure the dependence between a categorical random variable and a continuous variable.
Test of independence and feature screening for classification problems can be implemented via the two dependence measures.
For the details of the methods, see Zhong et al. (2023) <doi:10.1080/01621459.2023.2284988>;
Cui and Zhong (2019) <doi:10.1016/j.csda.2019.05.004>;
Cui, Li and Zhong (2015) <doi:10.1080/01621459.2014.920256>.
| Version: |
0.1.0 |
| Imports: |
energy, FNN, furrr, purrr, Rcpp, stats |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
testthat (≥ 3.0.0) |
| Published: |
2023-11-21 |
| DOI: |
10.32614/CRAN.package.semidist |
| Author: |
Wei Zhong [aut],
Zhuoxi Li [aut, cre, cph],
Wenwen Guo [aut],
Hengjian Cui [aut],
Runze Li [aut] |
| Maintainer: |
Zhuoxi Li <chainchei at gmail.com> |
| BugReports: |
https://github.com/wzhong41/semidist/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/wzhong41/semidist |
| NeedsCompilation: |
yes |
| Materials: |
README NEWS |
| CRAN checks: |
semidist results |
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