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>) and a repeated holdout validation WQS (Tanner et al. (2019) <doi:10.1016/j.mex.2019.11.008>) for continuous, binomial, multinomial, Poisson, quasi-Poisson and negative binomial outcomes.
Version: | 3.0.3 |
Depends: | R (≥ 3.5.0) |
Imports: | ggplot2, stats, broom, rlist, MASS, reshape2, plotROC, knitr, kableExtra, nnet, future, future.apply, pscl, ggrepel, cowplot |
Published: | 2021-02-04 |
Author: | Stefano Renzetti, Paul Curtin, Allan C Just, Ghalib Bello, Chris Gennings |
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 |
Reference manual: | gWQS.pdf |
Vignettes: |
How to use gWQS package |
Package source: | gWQS_3.0.3.tar.gz |
Windows binaries: | r-devel: gWQS_3.0.3.zip, r-release: gWQS_3.0.3.zip, r-oldrel: gWQS_3.0.3.zip |
macOS binaries: | r-release: gWQS_3.0.3.tgz, r-oldrel: gWQS_3.0.3.tgz |
Old sources: | gWQS archive |
Reverse imports: | lwqs |
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