bkmrhat: Parallel Chain Tools for Bayesian Kernel Machine Regression

Bayesian kernel machine regression (from the 'bkmr' package) is a Bayesian semi-parametric generalized linear model approach under identity and probit links. There are a number of functions in this package that extend Bayesian kernel machine regression fits to allow multiple-chain inference and diagnostics, which leverage functions from the 'future', 'rstan', and 'coda' packages. Reference: Bobb, J. F., Henn, B. C., Valeri, L., & Coull, B. A. (2018). Statistical software for analyzing the health effects of multiple concurrent exposures via Bayesian kernel machine regression. ; <doi:10.1186/s12940-018-0413-y>.

Version:	1.1.3
Depends:	coda, R (≥ 3.5.0)
Imports:	bkmr, data.table, future, rstan
Suggests:	knitr, markdown
Published:	2022-03-29
DOI:	10.32614/CRAN.package.bkmrhat
Author:	Alexander Keil [aut, cre]
Maintainer:	Alexander Keil <akeil at unc.edu>
License:	GPL (≥ 3)
NeedsCompilation:	no
Language:	en-US
Materials:	README NEWS
CRAN checks:	bkmrhat results

Documentation:

Reference manual:	bkmrhat.pdf
Vignettes:	The bkmrhat package: inference and diagnostics examples

Downloads:

Package source:	bkmrhat_1.1.3.tar.gz
Windows binaries:	r-devel: bkmrhat_1.1.3.zip, r-release: bkmrhat_1.1.3.zip, r-oldrel: bkmrhat_1.1.3.zip
macOS binaries:	r-release (arm64): bkmrhat_1.1.3.tgz, r-oldrel (arm64): bkmrhat_1.1.3.tgz, r-release (x86_64): bkmrhat_1.1.3.tgz, r-oldrel (x86_64): bkmrhat_1.1.3.tgz
Old sources:	bkmrhat archive

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