Package: bkmrhat 1.1.7

Alexander Keil

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>.

Authors:Alexander Keil [aut, cre]

bkmrhat_1.1.7.tar.gz
bkmrhat_1.1.7.zip(r-4.7)bkmrhat_1.1.7.zip(r-4.6)bkmrhat_1.1.7.zip(r-4.5)
bkmrhat_1.1.7.tgz(r-4.6-any)bkmrhat_1.1.7.tgz(r-4.5-any)
bkmrhat_1.1.7.tar.gz(r-4.7-any)bkmrhat_1.1.7.tar.gz(r-4.6-any)
bkmrhat_1.1.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bkmrhat/json (API)

# Install 'bkmrhat' in R:

install.packages('bkmrhat', repos = c('https://alexpkeil1.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/alexpkeil1/bkmrhat/issues

On CRAN:

4.92 score 7 stars 12 scripts 410 downloads 15 exports 76 dependencies

Last updated from:6b5ea188a9. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	231
source / vignettes	OK	278
linux-release-x86_64	OK	269
macos-release-arm64	OK	254
macos-oldrel-arm64	OK	246
windows-devel	OK	248
windows-release	OK	241
windows-oldrel	OK	241
wasm-release	OK	142

Exports:comb_bkmrfits comb_bkmrfits_lowmem ExtractPIPs_parallel kmbayes_combine kmbayes_combine_lowmem kmbayes_continue kmbayes_diag kmbayes_diagnose kmbayes_parallel kmbayes_parallel_continue OverallRiskSummaries_parallel PredictorResponseBivar_parallel PredictorResponseUnivar_parallel SamplePred_parallel SingVarRiskSummaries_parallel

Dependencies:abind backports BH bkmr callr checkmate cli coda codetools cpp11 data.table desc digest distributional dotCall64 dplyr farver fields future generics ggplot2 globals glue gmm gridExtra gtable inline isoband labeling lattice lifecycle listenv loo magrittr maps MASS Matrix matrixStats mvtnorm nlme numDeriv otel parallelly pillar pkgbuild pkgconfig posterior processx ps purrr QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel rlang rstan S7 sandwich scales spam StanHeaders stringi stringr tensorA tibble tidyr tidyselect tmvtnorm truncnorm utf8 vctrs viridisLite withr zoo

The bkmrhat package: diagnostics and multi-chain inference in Bayesian kernel machine regression

Introduction to bkmr and bkmrhat | How to use the bkmrhat package | Example 1: single vs multi-chains | Example 2: Diagnostics | Example 3: Posterior summaries | Example 4: diagnostics and inference when variable selection is used (Bayesian model averaging over the scale parameters of the kernel function) | Example 5: Parallel posterior summaries as diagnostics | Example 6: Continuing a fit | Acknowledgments

Rendered frombkmrhat-vignette.Rmdusingknitr::knitr

Last update: 2025-11-17
Started: 2020-08-30

Help page	Topics
Convert bkmrfit to mcmc object for coda MCMC diagnostics	as.mcmc.bkmrfit
Convert multi-chain bkmrfit to mcmc.list for coda MCMC diagnostics	as.mcmc.list.bkmrfit.list
Posterior inclusion probabilities by chain	ExtractPIPs_parallel
Combine multiple BKMR chains	comb_bkmrfits kmbayes_combine
Combine multiple BKMR chains in lower memory settings	comb_bkmrfits_lowmem kmbayes_combine_lowmem
Continue sampling from existing bkmr fit	kmbayes_continue
MCMC diagnostics using rstan	kmbayes_diag kmbayes_diagnose
Run multiple BKMR chains in parallel	kmbayes_parallel
Continue sampling from existing bkmr_parallel fit	kmbayes_parallel_continue
Overall summary by chain	OverallRiskSummaries_parallel
Posterior mean/sd predictions	predict.bkmrfit
Bivariate predictor response by chain	PredictorResponseBivar_parallel
Univariate predictor response summary by chain	PredictorResponseUnivar_parallel
Posterior samples of E(Y\|h(Z),X,beta) by chain	SamplePred_parallel
Single variable summary by chain	SingVarRiskSummaries_parallel

Package: bkmrhat 1.1.7

bkmrhat: Parallel Chain Tools for Bayesian Kernel Machine Regression

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)