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BDgraph

Overview

The R package BDgraph provides statistical tools for Bayesian structure learning for undirected graphical models with continuous, count, binary, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models' literature, including Mohammadi and Wit (2015), Mohammadi et al. (2021), Mohammadi et al. (2017), and Dobra and Mohammadi (2018). Besides, the package contains several functions for simulation and visualization, as well as several multivariate datasets taken from the literature. To speed up the computations, the computationally intensive tasks of the package are implemented in C++ in parallel using OpenMP.

Installation

You can install the latest version from CRAN using:

install.packages( "BDgraph" )

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library( BDgraph )

Simple Examples for BDgraph package

To see how to use the functionality of the package:

See also Mohammadi and Wit (2019).

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Version

Install

install.packages('BDgraph')

Monthly Downloads

2,168

Version

2.70

License

GPL (>= 2)

Maintainer

Abdolreza Mohammadi

Last Published

October 13th, 2022

Functions in BDgraph (2.70)

bdgraph.mpl

Search algorithm in graphical models using marginal pseudo-likehlihood
bdgraph.npn

Nonparametric transfer
bdgraph

Search algorithm in graphical models
bdgraph.dw

Search algorithm for Gaussian copula graphical models for count data
bdgraph.sim

Graph data simulation
bdw.reg

Bayesian estimation of (zero-inflated) Discrete Weibull regression
bf

Bayes factor between two graphs
adj2link

Extract links from an adjacency matrix
BDgraph-package

Bayesian Structure Learning in Graphical Models
churn

Churn data set
Discrete Weibull

The Discrete Weibull Distribution (Type 1)
geneExpression

Human gene expression dataset
pgraph

Posterior probabilities of the graphs
link2adj

Extract links from an adjacency matrix
conf.mat.plot

Plot Confusion Matrix
compare

Graph structure comparison
conf.mat

Confusion Matrix
gnorm

Normalizing constant for G-Wishart
graph.sim

Graph simulation
covariance

Estimated covariance matrix
plotroc

ROC plot
plot.bdgraph

Plot function for S3 class "bdgraph"
print.sim

Print function for S3 class "sim"
plotcoda

Convergence plot
precision

Estimated precision matrix
plinks

Estimated posterior link probabilities
plot.graph

Plot function for S3 class "graph"
reinis

Risk factors of coronary heart disease
print.bdgraph

Print function for S3 class "bdgraph"
plot.sim

Plot function for S3 class "sim"
summary.bdgraph

Summary function for S3 class "bdgraph"
rgwish

Sampling from G-Wishart distribution
traceplot

Trace plot of graph size
sparsity

Compute the sparsity of a graph
transfer

transfer for count data
surveyData

Labor force survey data
select

Graph selection
rmvnorm

Generate data from the multivariate Normal distribution
roc

Build a ROC curve
rwish

Sampling from Wishart distribution