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Quantitative characterization of the health impacts associated with exposure to chemical mixtures has received considerable attention in current environmental and epidemiological studies. 'CompMix' package allows practitioners to estimate the health impacts from exposure to chemical mixtures data through various statistical approaches, including Lasso, Elastic net, Bayesian kernel machine regression (BKMR), hierNet, Quantile g-computation, Weighted quantile sum (WQS) and Random forest. Methods and recommendations are described in Hao et al. (2025) <doi:10.1289/EHP15305>.
| Version: | 1.1.0 |
| Imports: | Matrix, mvtnorm, hierNet, glmnet, SuperLearner, bkmr, qgcomp, gWQS, pROC, randomForest |
| Published: | 2026-07-13 |
| DOI: | 10.32614/CRAN.package.CompMix |
| Author: | Wei Hao [aut, cre] |
| Maintainer: | Wei Hao <weihao at umich.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Citation: | CompMix citation info |
| Materials: | README |
| CRAN checks: | CompMix results |
| Reference manual: | CompMix.html , CompMix.pdf |
| Package source: | CompMix_1.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: CompMix_1.1.0.zip, r-oldrel: CompMix_1.1.0.zip |
| macOS binaries: | r-release (arm64): CompMix_1.1.0.tgz, r-oldrel (arm64): CompMix_1.1.0.tgz, r-release (x86_64): CompMix_1.1.0.tgz, r-oldrel (x86_64): CompMix_1.1.0.tgz |
| Old sources: | CompMix archive |
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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.