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-4.5-noble)groupWQS_0.0.3.tar.gz(r-4.4-noble)
groupWQS_0.0.3.tgz(r-4.4-emscripten)groupWQS_0.0.3.tgz(r-4.3-emscripten)
groupWQS.pdf |groupWQS.html✨
groupWQS/json (API)

# Install 'groupWQS' in R:
install.packages('groupWQS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • WQSdata - Simulated data of chemical concentrations and one continuous outcome variable
  • simdata - Simulated data of chemical concentrations and one binary outcome variable

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

2.00 score 4 scripts 169 downloads 1 mentions 4 exports 7 dependencies

Last updated 4 years agofrom:74d4ebee1f. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 16 2024
R-4.5-linuxNOTEOct 16 2024

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

Dependencies:codaglm2latticeMASSrjagsRsolnptruncnorm

groupWQS Vignette

Matthew Carli, Salem Rustom, David Wheeler

Rendered fromgroupWQS.Rmdusingknitr::rmarkdownon Oct 16 2024.

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