Learn R Programming

⚠️There's a newer version (2.73) of this package.Take me there.

BDgraph (version 2.13)

Graph estimation based on birth-death MCMC approach

Description

This package provides a Bayesian methodology for structure learning in undirected graphical models. Our Bayesian methodology is based on birth-death Markov chain Monte Carlo (BDMCMC) algorithm which is the main function with the name 'bdgraph'. The main target of this package is high-dimensional data analysis wherein usually p >> n. The computation is memory-optimized using the sparse matrix output.

Copy Link

Version

Install

install.packages('BDgraph')

Monthly Downloads

1,872

Version

2.13

License

GPL (>= 3)

Maintainer

Abdolreza Mohammadi

Last Published

November 17th, 2014

Functions in BDgraph (2.13)

BDgraph-package

Graph selection based on birth-death MCMC
I.g

Normalizing constant of G-Wishart distribution
bdgraph.npn

Nonparametric transfer
BDgraph-internal

Internal bdgraph functions and datasets
compare

Comparing the result
traceplot

Trace plot of graph size
surveyData

Labor force survey data
phat

Posterior edge inclusion probabilities
plot.simulate

Plot function for "bdgraph.sim" output
geneExpression

Human gene expression dataset
bdgraph

Graph selection based on birth-death MCMC algorithm
select

Selecting the best graph
print.simulate

Print function for "bdgraph.sim" output
CellSignal

A flow cytometry dataset
rgwish

Sampling from G-Wishart distribution
plot.bdgraph

Plot function for "bdgraph" output
print.bdgraph

Print function for "bdgraph" output
plotcoda

Convergence plot
summary.bdgraph

Summary function for "bdgraph" output
prob

Posterior probabilities of the graphs
bdgraph.sim

Synthetic graph data generator
plotroc

ROC plot