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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:

Reference manual: gWQS.pdf
Vignettes: How to use gWQS package

Downloads:

Package source: gWQS_3.0.5.tar.gz
Windows binaries: r-devel: gWQS_3.0.5.zip, r-release: gWQS_3.0.5.zip, r-oldrel: gWQS_3.0.5.zip
macOS binaries: r-release (arm64): gWQS_3.0.5.tgz, r-oldrel (arm64): gWQS_3.0.5.tgz, r-release (x86_64): gWQS_3.0.5.tgz, r-oldrel (x86_64): gWQS_3.0.5.tgz
Old sources: gWQS archive

Reverse dependencies:

Reverse imports: CompMix, lwqs, wqspt

Linking:

Please use the canonical form https://CRAN.R-project.org/package=gWQS to link to this page.

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.