gWQS

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.