Package: BayesGWQS 0.1.1

BayesGWQS: Bayesian Grouped Weighted Quantile Sum Regression

Fits Bayesian grouped weighted quantile sum (BGWQS) regressions for one or more chemical groups with binary outcomes. Wheeler DC et al. (2019) <doi:10.1016/j.sste.2019.100286>.

Authors:David Wheeler, Matthew Carli

BayesGWQS_0.1.1.tar.gz
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BayesGWQS_0.1.1.tgz(r-4.4-any)BayesGWQS_0.1.1.tgz(r-4.3-any)
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BayesGWQS.pdf |BayesGWQS.html
BayesGWQS/json (API)
NEWS

# Install 'BayesGWQS' in R:
install.packages('BayesGWQS', repos = c('https://mmcarli.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:
  • simdata - Simulated data of chemical concentrations and one binary outcome variable

On CRAN:

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

1.08 score 12 scripts 255 downloads 1 mentions 4 exports 13 dependencies

Last updated 3 years agofrom:cd612d26c0. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 21 2024
R-4.5-winNOTEOct 21 2024
R-4.5-linuxNOTEOct 21 2024
R-4.4-winNOTEOct 21 2024
R-4.4-macNOTEOct 21 2024
R-4.3-winNOTEOct 21 2024
R-4.3-macNOTEOct 21 2024

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

Dependencies:clicodagluelatticelifecyclemagrittrplyrRcpprjagsrlangstringistringrvctrs