Generalized Weighted Quantile Sum Regression

Fits Weighted Quantile Sum (WQS) regression (Carrico et al. (2014) ), a random subset implementation of WQS (Curtin et al. (2019) ) and a repeated holdout validation WQS (Tanner et al. (2019) ) for continuous, binomial, multinomial, Poisson, quasi-Poisson and negative binomial outcomes.


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install.packages("gWQS")

3.0.3 by Stefano Renzetti, 3 months ago


Browse source code at https://github.com/cran/gWQS


Authors: Stefano Renzetti , Paul Curtin , Allan C Just , Ghalib Bello , Chris Gennings


Documentation:   PDF Manual  


GPL (>= 2) license


Imports ggplot2, stats, broom, rlist, MASS, reshape2, plotROC, knitr, kableExtra, nnet, future, future.apply, pscl, ggrepel, cowplot


Imported by lwqs.


See at CRAN