Package: groupWQS 0.0.3

Matthew Carli

groupWQS: Grouped Weighted Quantile Sum Regression

Fits weighted quantile sum (WQS) regressions for one or more chemical groups with continuous or binary outcomes. Wheeler D, Czarnota J.(2016) <doi:10.1289/isee.2016.4698>.

Authors:David Wheeler, Matthew Carli

groupWQS_0.0.3.tar.gz
groupWQS_0.0.3.tar.gz(r-4.7-any)groupWQS_0.0.3.tar.gz(r-4.6-any)
groupWQS_0.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
groupWQS/json (API)

# Install 'groupWQS' in R:
install.packages('groupWQS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • simdata - Simulated data of chemical concentrations and one binary outcome variable
  • WQSdata - Simulated data of chemical concentrations and one continuous outcome variable

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

jagscpp

2.08 score 12 scripts 136 downloads 1 mentions 4 exports 17 dependencies

Last updated from:74d4ebee1f. Checks:2 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE128
source / vignettesOK245
linux-release-x86_64NOTE121
wasm-releaseOK153

Exports:gwqs.fitmake.Xmake.x.sweight.plot

Dependencies:codacodetoolsdigestfuturefuture.applyglm2globalslatticelistenvMASSnumDerivparallellyRcppRcppArmadillorjagsRsolnptruncnorm

groupWQS Vignette

Matthew Carli, Salem Rustom, David Wheeler

Rendered fromgroupWQS.Rmdusingknitr::rmarkdownon Jun 09 2026.

Last update: 2020-06-27
Started: 2020-06-17