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Title: BAREB: A Bayesian Repulsive Biclustering Model for Periodontal Data
Version: 1.0
Date: 2018-11-24
Author: Yuliang Li <yli193@jhu.edu>, Yanxun Xu <yxu.jhu@gmail.com>, Dipankar Bandyopadhyay <bandyopd@gmail.com>
Maintainer: Yuliang Li <yli193@jhu.edu>
Description: A Bayesian repulsive biclustering method 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 faciliate parsimony and interpretability. Essentially, BAREB is a cluster-wise linear model.