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BDgraph (version 2.18)

Graph Estimation 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

1,872

Version

2.18

License

GPL (>= 3)

Maintainer

Abdolreza Mohammadi

Last Published

April 19th, 2015

Functions in BDgraph (2.18)

rgwish

Sampling from G-Wishart distribution

plot.simulate

Plot function for S3 class "simulate"

compare

Comparing the result

phat

Posterior link probabilities

plotroc

ROC plot

plot.bdgraph

Plot function for S3 class "bdgraph"

geneExpression

Human gene expression dataset

traceplot

Trace plot of graph size

rwish

Sampling from Wishart distribution

summary.bdgraph

Summary function for S3 class "bdgraph"

print.bdgraph

Print function for S3 class "bdgraph"

BDgraph-package

Graph selection based on birth-death MCMC

select

Selecting the best graph

bdgraph.npn

Nonparametric transfer

surveyData

Labor force survey data

CellSignal

A flow cytometry dataset

print.simulate

Print function for S3 class "simulate"

BDgraph-internal

Internal BDgraph functions and datasets

bdgraph.sim

Synthetic graph data generator

plotcoda

Convergence plot

prob

Posterior probabilities of the graphs

bdgraph

Birth-death MCMC sampling algorithm for graphical models