BAREB: A Bayesian Repulsive Biclustering Model for Periodontal Data

BAREB, a BAyesian REpulsive Biclustering model, that can simultaneously cluster the Periodontal diseases (PD) patients and their tooth sites after taking the patient- and site-level covariates into consideration. BAREB uses the determinantal point process (DPP) prior to induce diversity among different biclusters to facilitate parsimony and interpretability. Essentially, BAREB is a cluster-wise linear model based on Yuliang (2019) <arXiv:1902.05680>.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo
Published: 2020-03-06
Author: Yuliang Li [aut, cre], Yanxun Xu [aut], Dipankar Bandyopadhyay [aut], John Burkardt [ctb]
Maintainer: Yuliang Li <yli193 at jhu.edu>
License: GPL-3
NeedsCompilation: yes
CRAN checks: BAREB results

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Reference manual: BAREB.pdf
Package source: BAREB_0.1.0.tar.gz
Windows binaries: r-devel: BAREB_0.1.0.zip, r-devel-gcc8: BAREB_0.1.0.zip, r-release: BAREB_0.1.0.zip, r-oldrel: BAREB_0.1.0.zip
OS X binaries: r-release: BAREB_0.1.0.tgz, r-oldrel: BAREB_0.1.0.tgz

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