Package: mixedBayes
Type: Package
Title: Bayesian Longitudinal Regularized Quantile Mixed Model
Version: 0.2.5
Date: 2026-04-23
Authors@R: c( person("Kun", "Fan", role = c("aut", "cre") , email = "fzt0428@gmail.com"),
              person("Shejuty", "Devnath", role = "aut"),
              person("Cen", "Wu", role = "aut"))
Description: 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.
Depends: R (>= 4.2.0)
License: GPL-2
Encoding: UTF-8
URL: https://github.com/kunfa/mixedBayes
BugReports: https://github.com/kunfa/mixedBayes/issues
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.3.3
Repository: https://kunfa.r-universe.dev
Date/Publication: 2026-04-23 06:12:10 UTC
RemoteUrl: https://github.com/kunfa/mixedbayes
RemoteRef: HEAD
RemoteSha: a95eeaa266e3c3de05f030b8c01ac6280960d7a9
NeedsCompilation: yes
Packaged: 2026-06-22 11:41:23 UTC; root
Author: Kun Fan [aut, cre],
  Shejuty Devnath [aut],
  Cen Wu [aut]
Maintainer: Kun Fan <fzt0428@gmail.com>