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: 0.1.16
Depends: coda, R (≥ 3.5.0)
Imports: bkmr, future, rstan
Suggests: knitr, markdown
Published: 2020-09-16
Author: Alexander Keil [aut, cre]
Maintainer: Alexander Keil <akeil at unc.edu>
License: GPL (≥ 3)
NeedsCompilation: no
Language: en-US
Materials: NEWS
CRAN checks: bkmrhat results

Downloads:

Reference manual: bkmrhat.pdf
Vignettes: The bkmrhat package: inference and diagnostics examples
Package source: bkmrhat_0.1.16.tar.gz
Windows binaries: r-devel: bkmrhat_0.1.16.zip, r-release: bkmrhat_0.1.16.zip, r-oldrel: bkmrhat_0.1.16.zip
macOS binaries: r-release: bkmrhat_0.1.16.tgz, r-oldrel: bkmrhat_0.1.16.tgz

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