Introduction | Using groupWQS | Data Preparation | Model Fitting | Examining Individual Component Weights
This package is considered a duplicate. The official version of this package is found at:https://mmcarli.r-universe.dev/groupWQS
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:
groupWQS_0.0.3.tar.gz
groupWQS_0.0.3.zip(r-4.7-any)groupWQS_0.0.3.zip(r-4.6-any)
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✨
DESCRIPTION
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')) |
Datasets:
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:74d4ebee1f. Checks:4 NOTE, 2 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | NOTE | 111 | ||
| source / vignettes | OK | 201 | ||
| linux-release | NOTE | 138 | ||
| windows-devel | NOTE | 81 | ||
| windows-release | NOTE | 82 | ||
| wasm-release | OK | 90 |
Exports:gwqs.fitmake.Xmake.x.sweight.plot
Dependencies:codacodetoolsdigestfuturefuture.applyglm2globalslatticelistenvMASSnumDerivparallellyRcppRcppArmadillorjagsRsolnptruncnorm
