gWQS
Generalized Weighted Quantile Sum Regression
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
3.0.5 |
rolling source/ R- | gWQS_3.0.5.tar.gz |
1.6 MiB |
3.0.5 |
rolling linux/jammy R-4.5 | gWQS_3.0.5.tar.gz |
2.0 MiB |
3.0.5 |
rolling linux/noble R-4.5 | gWQS_3.0.5.tar.gz |
2.0 MiB |
3.0.5 |
latest source/ R- | gWQS_3.0.5.tar.gz |
1.6 MiB |
3.0.5 |
latest linux/jammy R-4.5 | gWQS_3.0.5.tar.gz |
2.0 MiB |
3.0.5 |
latest linux/noble R-4.5 | gWQS_3.0.5.tar.gz |
2.0 MiB |
3.0.5 |
2026-04-23 source/ R- | gWQS_3.0.5.tar.gz |
1.6 MiB |
3.0.5 |
2026-04-09 windows/windows R-4.5 | gWQS_3.0.5.zip |
2.0 MiB |
3.0.5 |
2025-04-20 source/ R- | gWQS_3.0.5.tar.gz |
1.6 MiB |