simBKMRdata: Helper Functions for Bayesian Kernel Machine Regression

Provides a suite of helper functions to support Bayesian Kernel Machine Regression (BKMR) analyses in environmental health research. It enables the simulation of realistic multivariate exposure data using Multivariate Skewed Gamma distributions, estimation of distributional parameters by subgroup, and application of adaptive, data-driven thresholds for feature selection via Posterior Inclusion Probabilities (PIPs). It is especially suited for handling skewed exposure data and enhancing the interpretability of BKMR results through principled variable selection. The methodology is shown in Hasan et. al. (2025) <doi:10.1101/2025.04.14.25325822>.

Version:	0.1.1
Depends:	R (≥ 3.5)
Imports:	MASS, stats
Suggests:	bkmr, fields, gt, quarto, testthat (≥ 3.0.0), tidyverse
Published:	2025-04-22
DOI:	10.32614/CRAN.package.simBKMRdata
Author:	Kazi Tanvir Hasan [aut, cre], Gabriel Odom [aut], Roberto Lucchini [ctb]
Maintainer:	Kazi Tanvir Hasan <khasa006 at fiu.edu>
License:	GPL (≥ 3)
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	simBKMRdata results

Documentation:

Reference manual:	simBKMRdata.pdf
Vignettes:	Calculate PIP Threshold from Response Vector (source, R code) Simulation and Estimation for each group (source, R code) simBKMR R Package (source, R code)

Downloads:

Package source:	simBKMRdata_0.1.1.tar.gz
Windows binaries:	r-devel: not available, r-release: simBKMRdata_0.1.1.zip, r-oldrel: simBKMRdata_0.1.1.zip
macOS binaries:	r-release (arm64): simBKMRdata_0.1.1.tgz, r-oldrel (arm64): simBKMRdata_0.1.1.tgz, r-release (x86_64): simBKMRdata_0.1.1.tgz, r-oldrel (x86_64): simBKMRdata_0.1.1.tgz

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