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.


Reference manual

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3.0.4 by Stefano Renzetti, 5 months ago

Browse source code at

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

Documentation:   PDF Manual  

GPL (>= 2) license

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

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Imported by lwqs.

See at CRAN