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BDgraph (version 2.19)

Bayesian Graph Selection Based on Birth-Death MCMC Approach

Description

A general framework to perform Bayesian structure learning in undirected graphical models. The main target is high-dimensional data analysis wherein either continuous or discrete variables.

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Version

Install

install.packages('BDgraph')

Monthly Downloads

1,909

Version

2.19

License

GPL (>= 3)

Maintainer

Abdolreza Mohammadi

Last Published

June 16th, 2015

Functions in BDgraph (2.19)

bdgraph.npn

Nonparametric transfer

rgwish

Sampling from G-Wishart distribution

surveyData

Labor force survey data

rwish

Sampling from Wishart distribution

geneExpression

Human gene expression dataset

I.g

Normalizing constant of G-Wishart distribution

traceplot

Trace plot of graph size

plot.bdgraph

Plot function for S3 class "bdgraph"

summary.bdgraph

Summary function for S3 class "bdgraph"

compare

Comparing the result

plot.simulate

Plot function for S3 class "simulate"

Print function for S3 class "simulate"

bdgraph.sim

Synthetic graph data generator

select

Selecting the best graph

BDgraph-internal

Internal BDgraph functions and datasets

prob

Posterior probabilities of the graphs

bdgraph

Birth-death MCMC sampling algorithm for graphical models

CellSignal

A flow cytometry dataset

print.bdgraph

Print function for S3 class "bdgraph"

BDgraph-package

Graph selection based on birth-death MCMC

phat

Posterior link probabilities