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BDgraph (version 2.22)

Bayesian Graph Selection Based on Birth-Death MCMC Approach

Description

Bayesian inference for structure learning in undirected graphical models. The main target is to uncover complicated patterns in multivariate data wherein either continuous or discrete variables.

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Version

Install

install.packages('BDgraph')

Monthly Downloads

1,909

Version

2.22

License

GPL (>= 3)

Maintainer

Abdolreza Mohammadi

Last Published

August 31st, 2015

Functions in BDgraph (2.22)

print.sim

Print function for S3 class "sim"

I.g

Normalizing constant of G-Wishart distribution

geneExpression

Human gene expression dataset

surveyData

Labor force survey data

print.bdgraph

Print function for S3 class "bdgraph"

rgwish

Sampling from G-Wishart distribution

BDgraph-package

Graph selection based on birth-death MCMC

phat

Posterior link probabilities

CellSignal

A flow cytometry dataset

bdgraph

Birth-death MCMC sampling algorithm for graphical models

bdgraph.npn

Nonparametric transfer

summary.bdgraph

Summary function for S3 class "bdgraph"

rwish

Sampling from Wishart distribution

compare

Comparing the result

plot.sim

Plot function for S3 class "sim"

BDgraph-internal

Internal BDgraph functions and datasets

plotroc

ROC plot

bdgraph.sim

Synthetic graph data generator

plot.bdgraph

Plot function for S3 class "bdgraph"

prob

Posterior probabilities of the graphs

traceplot

Trace plot of graph size

plotcoda

Convergence plot

select

Selecting the best graph