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Provides statistical tools for evaluating how covariates influence the strength of Pearson correlation coefficients between two response variables. Supports bivariate normal and bivariate binary responses, with likelihood-based inference and bootstrap-based significance testing. The methodology is based on Dufera, Liu and Xu (2023) "Regression models of Pearson correlation coefficient" <doi:10.1080/24754269.2023.2164970>.
| Version: | 0.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | stats |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2026-06-03 |
| DOI: | 10.32614/CRAN.package.regcorr |
| Author: | Ze Lin [aut, cre], Bo Li [aut], Jinyao Shen [aut] |
| Maintainer: | Ze Lin <zlin5858 at 163.com> |
| BugReports: | https://github.com/lonze-nb/regcorr/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/lonze-nb/regcorr |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | regcorr results |
| Reference manual: | regcorr.html , regcorr.pdf |
| Package source: | regcorr_0.1.0.tar.gz |
| Windows binaries: | r-devel: regcorr_0.1.0.zip, r-release: regcorr_0.1.0.zip, r-oldrel: regcorr_0.1.0.zip |
| macOS binaries: | r-release (arm64): regcorr_0.1.0.tgz, r-oldrel (arm64): regcorr_0.1.0.tgz, r-release (x86_64): regcorr_0.1.0.tgz, r-oldrel (x86_64): regcorr_0.1.0.tgz |
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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.