gWQSRS: Generalized Weighted Quantile Sum Regression Random Subset

Fits Weighted Quantile Sum Random Subset (WQSRS) regressions for continuous, binomial, multinomial and count outcomes. Paul Curtin, Joshua Kellogg, Nadja Cech, Chris Gennings (2019) <doi:10.1080/03610918.2019.1577971>.

Version: 1.0.0
Imports: Rsolnp, gWQS (≥ 2.0.0), ggplot2, dplyr, stats, broom, rlist, MASS, reshape2, plotROC, knitr, kableExtra, nnet, future, future.apply, ggrepel, pscl
Published: 2019-08-30
Author: Stefano Renzetti, Paul Curtin, Chris Gennings
Maintainer: Stefano Renzetti <stefano.renzetti88 at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: gWQSRS results

Downloads:

Reference manual: gWQSRS.pdf
Package source: gWQSRS_1.0.0.tar.gz
Windows binaries: r-devel: gWQSRS_1.0.0.zip, r-devel-gcc8: gWQSRS_1.0.0.zip, r-release: gWQSRS_1.0.0.zip, r-oldrel: gWQSRS_1.0.0.zip
OS X binaries: r-release: gWQSRS_1.0.0.tgz, r-oldrel: gWQSRS_1.0.0.tgz

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