Package: bayesMRM 2.4.0

bayesMRM: Bayesian Multivariate Receptor Modeling

Bayesian analysis of multivariate receptor modeling. The package consists of implementations of the methods of Park and Oh (2015) <doi:10.1016/j.chemolab.2015.08.021>.The package uses 'JAGS'(Just Another Gibbs Sampler) to generate Markov chain Monte Carlo samples of parameters.

Authors:Man-Suk Oh [aut, cre], Eun-Kyung Lee [aut], Eun Sug Park [aut]

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bayesMRM.pdf |bayesMRM.html✨
bayesMRM/json (API)

# Install 'bayesMRM' in R:
install.packages('bayesMRM', repos = c('https://mansukoh.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:
  • Elpaso - PM2.5 speciation data from El Paso, Texas, USA.

On CRAN:

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

1.00 score 308 downloads 5 exports 64 dependencies

Last updated 2 years agofrom:1282e61a92. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-winOKNov 16 2024
R-4.5-linuxOKNov 16 2024
R-4.4-winOKNov 16 2024
R-4.4-macOKNov 16 2024
R-4.3-winOKNov 16 2024
R-4.3-macOKNov 16 2024

Exports:bayesMRMAppbmrmconvdiag_bmrmpcplottrace_ACF_plot

Dependencies:base64encbslibcachemclicodacolorspacecommonmarkcrayondigestevaluatefansifarverfastmapfontawesomefsggplot2gluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvisobandjquerylibjsonliteknitrlabelinglaterlatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmepillarpkgconfigpromisesR6rappdirsRColorBrewerRcpprglrjagsrlangrmarkdownsassscalesshinyshinythemessourcetoolstibbletinytexutf8vctrsviridisLitewithrxfunxtableyaml