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BGGM (version 2.1.6)

Bayesian Gaussian Graphical Models

Description

Fit Bayesian Gaussian graphical models. The methods are separated into two Bayesian approaches for inference: hypothesis testing and estimation. There are extensions for confirmatory hypothesis testing, comparing Gaussian graphical models, and node wise predictability. These methods were recently introduced in the Gaussian graphical model literature, including Williams (2019) , Williams and Mulder (2019) , Williams, Rast, Pericchi, and Mulder (2019) .

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Version

Install

install.packages('BGGM')

Monthly Downloads

930

Version

2.1.6

License

GPL-2

Maintainer

Philippe Rast

Last Published

December 2nd, 2025

Functions in BGGM (2.1.6)

Compute Regression Parameters for explore Objects

Data: Autism and Obssesive Compulsive Disorder

GGM: Confirmatory Hypothesis Testing

Compute Posterior Distributions from Graph Search Results

Data: Sachs Network

Simulate a Partial Correlation Matrix

Data: Contingencies of Self-Worth Scale (CSWS)

Fisher Z Transformation

Generate Ordinal and Binary data

MCMC Convergence

Fisher Z Back Transformation

GGM: Exploratory Hypothesis Testing

GGM: Estimation

depression_anxiety_t1

Data: Depression and Anxiety (Time 1)

depression_anxiety_t2

Data: Depression and Anxiety (Time 2)

Maximum A Posteriori Precision Matrix

Perform Bayesian Graph Search and Optional Model Averaging

ggm_compare_explore

GGM Compare: Exploratory Hypothesis Testing

Data: ifit Intensive Longitudinal Data

Data: Interpersonal Reactivity Index (IRI)

Data: 1994 General Social Survey

Obtain Imputed Datasets

plot.predictability

Plot predictability Objects

Network Plot for select Objects

plot.summary.estimate

Plot summary.estimate Objects

plot.roll_your_own

Plot roll_your_own Objects

ggm_compare_confirm

GGM Compare: Confirmatory Hypothesis Testing

Extract the Partial Correlation Matrix

Partial Correlation Sum

ggm_compare_estimate

GGM Compare: Estimate

plot.summary.ggm_compare_estimate

Plot summary.ggm_compare_estimate Objects

plot.summary.explore

Plot summary.explore Objects

Precision Matrix Posterior Distribution

predict.estimate

Model Predictions for estimate Objects

Plot pcor_sum Object

plot.ggm_compare_ppc

Plot ggm_compare_ppc Objects

ggm_compare_ppc

GGM Compare: Posterior Predictive Check

Predictability: Bayesian Variance Explained (R2)

Data: Post-Traumatic Stress Disorder (Sample # 1)

Plot confirm objects

plot.summary.var_estimate

Plot summary.var_estimate Objects

Compute Correlations from the Partial Correlations

plot.summary.ggm_compare_explore

Plot summary.ggm_compare_explore Objects

Plot: Prior Distribution

Data: Post-Traumatic Stress Disorder (Sample # 2)

predicted_probability

Predicted Probabilities

plot.summary.select.explore

Plot summary.select.explore Objects

Print method for BGGM objects

prior_belief_ggm

Prior Belief Gaussian Graphical Model

posterior_predict

Posterior Predictive Distribution

posterior_samples

Extract Posterior Samples

prior_belief_var

Prior Belief Graphical VAR

Data: Post-Traumatic Stress Disorder (Sample # 3)

Data: Post-Traumatic Stress Disorder

select.ggm_compare_explore

Graph selection for ggm_compare_explore Objects

select.ggm_compare_estimate

Graph Selection for ggm_compare_estimate Objects

predict.var_estimate

Model Predictions for var_estimate Objects

predict.explore

Model Predictions for explore Objects

summary.ggm_compare_estimate

Summary method for ggm_compare_estimate objects

summary.ggm_compare_explore

Summary Method for ggm_compare_explore Objects

Graph selection for explore Objects

select.estimate

Graph Selection for estimate Objects

select.var_estimate

Graph Selection for var.estimate Object

summary.predictability

Summary Method for predictability Objects

regression_summary

Summarary Method for Multivariate or Univarate Regression

Compute Custom Network Statistics

zero_order_cors

Zero-Order Correlations

Data: Women and Mathematics

Summarize coef Objects

Data: Toronto Alexithymia Scale (TAS)

summary.var_estimate

Summary Method for var_estimate Objects

summary.select.explore

Summary Method for select.explore Objects

Data: Post-Traumatic Stress Disorder (Sample # 4)

weighted_adj_mat

Extract the Weighted Adjacency Matrix

VAR: Estimation

S3 select method

Data: Resilience Scale of Adults (RSA)

summary.explore

Summary Method for explore.default Objects

summary.estimate

Summary method for estimate.default objects

constrained_posterior

Constrained Posterior Distribution

GGM: Missing Data

Compute Regression Parameters for estimate Objects

Data: 25 Personality items representing 5 factors

BGGM: Bayesian Gaussian Graphical Models