semidist: Measure Dependence Between Categorical and Continuous Variables (original) (raw)
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 |
| BugReports: | https://github.com/wzhong41/semidist/issues |
| License: | MIT + file |
| URL: | https://github.com/wzhong41/semidist |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | semidist results |
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