alexpkeil1/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>.

Getting started

Package details

AuthorAlexander Keil [aut, cre]
MaintainerAlexander Keil <akeil@unc.edu>
LicenseGPL (>= 3)
Version1.1.3
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("alexpkeil1/bkmrhat")
alexpkeil1/bkmrhat documentation built on April 2, 2022, 8:43 a.m.