mixedBayes: Bayesian Longitudinal Regularized Quantile Mixed Model

With high-dimensional omics features, repeated measure ANOVA leads to longitudinal gene-environment interaction studies that have intra-cluster correlations, outlying observations and structured sparsity arising from the ANOVA design. In this package, we have developed robust sparse Bayesian mixed effect models tailored for the above studies (Fan et al. (2025) <doi:10.1093/jrsssc/qlaf027>). An efficient Gibbs sampler has been developed to facilitate fast computation. The Markov chain Monte Carlo algorithms of the proposed and alternative methods are efficiently implemented in 'C++'. The development of this software package and the associated statistical methods have been partially supported by an Innovative Research Award from Johnson Cancer Research Center, Kansas State University.

Version: 0.1.7
Depends: R (≥ 4.2.0)
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo
Published: 2025-05-01
DOI: 10.32614/CRAN.package.mixedBayes
Author: Kun Fan [aut, cre], Cen Wu [aut]
Maintainer: Kun Fan <kfan at ksu.edu>
License: GPL-2
URL: https://github.com/kunfa/mixedBayes
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: mixedBayes results

Documentation:

Reference manual: mixedBayes.pdf

Downloads:

Package source: mixedBayes_0.1.7.tar.gz
Windows binaries: r-devel: mixedBayes_0.1.6.zip, r-release: mixedBayes_0.1.7.zip, r-oldrel: mixedBayes_0.1.7.zip
macOS binaries: r-release (arm64): mixedBayes_0.1.7.tgz, r-oldrel (arm64): mixedBayes_0.1.7.tgz, r-release (x86_64): mixedBayes_0.1.7.tgz, r-oldrel (x86_64): mixedBayes_0.1.7.tgz
Old sources: mixedBayes archive

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