Fits bivariate logistic Box-Cox regression models for binary outcomes and positive continuous predictors. Transformation parameters are selected by cross-validated grid search with adaptive refinement and thin-plate spline smoothing. The package also provides prediction, empirical and sampling-weighted median effects, simulation tools, and sampling-weighted model fitting. The methodology extends the logistic Box-Cox approach of Xing et al. (2021) <doi:10.1002/cjs.11587>.
| Version: | 0.1.4 |
| Imports: | methods, stats, parallel, fields |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: | 2026-08-26 |
| DOI: | 10.32614/CRAN.package.mvboxcox (may not be active yet) |
| Author: | Shiyu Xu [aut], Xuekui Zhang [aut, cre] |
| Maintainer: | Xuekui Zhang <ubcxzhang at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | mvboxcox results |
| Reference manual: | mvboxcox.html , mvboxcox.pdf |
| Vignettes: |
Bivariate Logistic Box-Cox Regression with mvboxcox (source, R code) |
| Package source: | mvboxcox_0.1.4.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): mvboxcox_0.1.4.tgz, r-oldrel (arm64): mvboxcox_0.1.4.tgz, r-release (x86_64): mvboxcox_0.1.4.tgz, r-oldrel (x86_64): mvboxcox_0.1.4.tgz |
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