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BAREB (version 0.1.2)

A Bayesian Repulsive Biclustering Model for Periodontal Data

Description

Simultaneously clusters 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 (2020) .

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Version

Install

install.packages('BAREB')

Monthly Downloads

225

Version

0.1.2

License

GPL-3

Maintainer

Qingyang Liu

Last Published

December 18th, 2024

Functions in BAREB (0.1.2)

Function to update patient level linear coefficients in the BAREB model

Function to update site level clustering in the BAREB model

Function to generate new latent values for missingness model

Function to update estimated mean CAL values based on current parameters

Function to update mean latent values for missingness model

update_sigma_squre

update_sigma_squre

Function to update the number of site level clusters for one patient level cluster via RJMCMC

The function to get the kernel function value

Function to update the number of site level clusters for one patient level cluster via RJMCMC, when there is no patient in this cluster

The simulation truth

The simulation observation

The BAREB package: summary information

The initial value of patient- and site-level covariates for simulation

Function to update c in missingess model

Function to update patient level clustering in the BAREB model

Function to obtain the kernel matrix of the determinantal point process

Function to update site level linear coefficients in the BAREB model

update_theta_beta

update_theta_beta

update_theta_gamma

update_theta_gamma