Parallel Chain Tools for Bayesian Kernel Machine Regression
Convert bkmrfit to mcmc object for coda MCMC diagnostics
Convert multi-chain bkmrfit to mcmc.list for coda MCMC diagnostics
Posterior inclusion probabilities by chain
Combine multiple BKMR chains in lower memory settings
Combine multiple BKMR chains
Continue sampling from existing bkmr fit
MCMC diagnostics using rstan
Continue sampling from existing bkmr_parallel fit
Run multiple BKMR chains in parallel
Overall summary by chain
Posterior mean/sd predictions
Bivariate predictor response by chain
Univariate predictor response summary by chain
Posterior samples of E(Y|h(Z),X,beta) by chain
Single variable summary by chain
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>.