Package: BAREB 0.1.2

BAREB: A Bayesian Repulsive Biclustering Model for Periodontal Data

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) <doi:10.1002/sim.8536>.

Authors:Yuliang Li [aut], Yanxun Xu [aut], Dipankar Bandyopadhyay [aut], John Burkardt [ctb], Qingyang Liu [aut, cre]

BAREB_0.1.2.tar.gz
BAREB_0.1.2.zip(r-4.7)BAREB_0.1.2.zip(r-4.6)BAREB_0.1.2.zip(r-4.5)
BAREB_0.1.2.tgz(r-4.6-x86_64)BAREB_0.1.2.tgz(r-4.6-arm64)BAREB_0.1.2.tgz(r-4.5-x86_64)BAREB_0.1.2.tgz(r-4.5-arm64)
BAREB_0.1.2.tar.gz(r-4.7-arm64)BAREB_0.1.2.tar.gz(r-4.7-x86_64)BAREB_0.1.2.tar.gz(r-4.6-arm64)BAREB_0.1.2.tar.gz(r-4.6-x86_64)
BAREB_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BAREB/json (API)

# Install 'BAREB' in R:

install.packages('BAREB', repos = c('https://rh8liuqy.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

Init - The initial value of patient- and site-level covariates for simulation
obs - The simulation observation
truth - The simulation truth

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas cpp openmp

1.00 score 3 scripts 203 downloads 20 exports 2 dependencies

Last updated from:6112efd66d. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	128
linux-devel-x86_64	OK	114
source / vignettes	OK	146
linux-release-arm64	OK	118
linux-release-x86_64	OK	110
macos-release-arm64	OK	121
macos-release-x86_64	OK	288
macos-oldrel-arm64	OK	102
macos-oldrel-x86_64	OK	172
windows-devel	OK	155
windows-release	OK	131
windows-oldrel	OK	151
wasm-release	OK	128

Exports:const kernelC likeli_theta RJi RJi_empty update_RJ update_sigma_squre update_theta_beta update_theta_gamma update_w update_w_beta updateBeta updatec updateC updateE updateGamma updatemu updatemustar updateR updateZstar

Dependencies:Rcpp RcppArmadillo

Help page	Topics
The BAREB package: summary information	BAREB
const	const
The initial value of patient- and site-level covariates for simulation	Init
The function to get the kernel function value	kernelC
likeli_theta	likeli_theta
The simulation observation	obs
Function to update the number of site level clusters for one patient level cluster via RJMCMC	RJi
Function to update the number of site level clusters for one patient level cluster via RJMCMC, when there is no patient in this cluster	RJi_empty
The simulation truth	truth
update_RJ	update_RJ
update_sigma_squre	update_sigma_squre
update_theta_beta	update_theta_beta
update_theta_gamma	update_theta_gamma
update_w	update_w
update_w_beta	update_w_beta
Function to update patient level linear coefficients in the BAREB model	updateBeta
Function to update c in missingess model	updatec
Function to obtain the kernel matrix of the determinantal point process	updateC
Function to update patient level clustering in the BAREB model	updateE
Function to update site level linear coefficients in the BAREB model	updateGamma
Function to update estimated mean CAL values based on current parameters	updatemu
Function to update mean latent values for missingness model	updatemustar
Function to update site level clustering in the BAREB model	updateR
Function to generate new latent values for missingness model	updateZstar

Package: BAREB 0.1.2

BAREB: A Bayesian Repulsive Biclustering Model for Periodontal Data

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)