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


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


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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