gWQS: Generalized Weighted Quantile Sum Regression
Fits Weighted Quantile Sum (WQS) regression (Carrico et al. (2014) <doi:10.1007/s13253-014-0180-3>), a random subset implementation of WQS (Curtin et al. (2019) <doi:10.1080/03610918.2019.1577971>), a repeated holdout validation WQS (Tanner et al. (2019) <doi:10.1016/j.mex.2019.11.008>) and a WQS with 2 indices (Renzetti et al. (2023) <doi:10.3389/fpubh.2023.1289579>) for continuous, binomial, multinomial, Poisson, quasi-Poisson and negative binomial outcomes.
| Version: | 3.0.5 |
| Depends: | R (≥ 3.5.0) |
| Imports: | ggplot2, stats,broom,rlist,MASS,reshape2,plotROC,knitr,kableExtra,nnet,future,future.apply,pscl,ggrepel,cowplot,Matrix,car, utils,bookdown |
| Suggests: | markdown |
| Published: | 2023-11-16 |
| DOI: | 10.32614/CRAN.package.gWQS |
| Author: | Stefano Renzetti [aut, cre], Paul Curtin [aut], Allan C Just [ctb], Ghalib Bello [ctb], Chris Gennings [aut] |
| Maintainer: | Stefano Renzetti <stefano.renzetti88 at gmail.com> |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | gWQS results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=gWQSto link to this page.