SamplePred_parallel

bkmrfit.list object from <code><a rd-options="bkmrhat" href="/link/kmbayes_parallel?package=bkmrhat&version=0.1.16&to=bkmrhat" data-mini-rdoc="bkmrhat::kmbayes_parallel">kmbayes_parallel</a></code>

arguments to <code><a rd-options="bkmr" href="/link/CalcPIPs?package=bkmrhat&version=0.1.16&to=bkmr" data-mini-rdoc="bkmr::CalcPIPs">CalcPIPs</a></code>

Posterior samples of E(Y|h(Z),X,beta) 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>.

Alexander Keil

bkmrhat

Parallel Chain Tools for Bayesian Kernel Machine Regression

SamplePred_parallel function

bkmrfit.list object from <code><a rd-options='bkmrhat' href='kmbayes_parallel'>kmbayes_parallel</a></code>

arguments to <code><a rd-options='bkmr' href='CalcPIPs'>CalcPIPs</a></code>

SamplePred_parallel: Posterior samples of E(Y|h(Z),X,beta) by chain

Description

Usage

Arguments

Value