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BDgraph (version 2.62)

Bayesian Structure Learning in Graphical Models using Birth-Death MCMC

Description

Statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) , Mohammadi and Wit (2019) .

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Version

Install

install.packages('BDgraph')

Monthly Downloads

1,822

Version

2.62

License

GPL (>= 2)

Maintainer

Abdolreza Mohammadi

Last Published

December 5th, 2019

Functions in BDgraph (2.62)

Search algorithm in graphical models

Convergence plot

Print function for S3 class "sim"

Print function for S3 class "bdgraph"

Plot function for S3 class "sim"

Estimated posterior link probabilities

Posterior probabilities of the graphs

Sampling from Wishart distribution

Generate data from the multivariate Normal distribution

Search algorithm in graphical models using marginal pseudo-likehlihood

Plot function for S3 class "bdgraph"

Plot function for S3 class "graph"

Graph simulation

Human gene expression dataset

Normalizing constant for G-Wishart

Estimated precision matrix

Trace plot of graph size

Labor force survey data

Graph selection

Extract links from an adjacency matrix

Risk factors of coronary heart disease

Sampling from G-Wishart distribution

transfer for discrete data

summary.bdgraph

Summary function for S3 class "bdgraph"

Graph structure comparison

Nonparametric transfer

BDgraph-package

Bayesian Structure Learning in Graphical Models

Estimated covariance matrix

Graph data simulation

Bayes factor between two graphs

Extract links from an adjacency matrix