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mvboxcox: Bivariate Logistic Box-Cox Regression

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
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

Documentation:

Reference manual: mvboxcox.html , mvboxcox.pdf
Vignettes: Bivariate Logistic Box-Cox Regression with mvboxcox (source, R code)

Downloads:

Package source: mvboxcox_0.1.4.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: mvboxcox_0.1.4.zip
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

Linking:

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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.