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BGGM (version 2.2.0)

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

745

Version

2.2.0

License

GPL-2

Maintainer

Philippe Rast

Last Published

September 24th, 2026

Functions in BGGM (2.2.0)

depression_anxiety_t2

Data: Depression and Anxiety (Time 2)
iri

Data: Interpersonal Reactivity Index (IRI)
gss

Data: 1994 General Social Survey
ggm_search

Perform Bayesian Graph Search and Optional Model Averaging
ggm_compare_ppc

GGM Compare: Posterior Predictive Check
ggm_compare_explore

GGM Compare: Exploratory Hypothesis Testing
plot.pcor_sum

Plot pcor_sum Object
plot.ggm_compare_ppc

Plot ggm_compare_ppc Objects
plot.confirm

Plot confirm objects
ggm_compare_confirm

GGM Compare: Confirmatory Hypothesis Testing
ifit

Data: ifit Intensive Longitudinal Data
pcor_mat

Extract the Partial Correlation Matrix
impute_data

Obtain Imputed Datasets
pcor_sum

Partial Correlation Sum
plot.summary.explore

Plot summary.explore Objects
ggm_compare_estimate

GGM Compare: Estimate
pcor_to_cor

Compute Correlations from the Partial Correlations
plot.roll_your_own

Plot roll_your_own Objects
predict.estimate

Model Predictions for estimate Objects
plot.predictability

Plot predictability Objects
precision

Precision Matrix Posterior Distribution
plot.summary.ggm_compare_estimate

Plot summary.ggm_compare_estimate Objects
posterior_samples

Extract Posterior Samples
ptsd_cor2

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

Posterior Predictive Distribution
predicted_probability

Predicted Probabilities
ptsd_cor1

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

Predictability: Bayesian Variance Explained (R2)
predict.explore

Model Predictions for explore Objects
regression_summary

Summarary Method for Multivariate or Univarate Regression
roll_your_own

Compute Custom Network Statistics
plot.summary.ggm_compare_explore

Plot summary.ggm_compare_explore Objects
predict.var_estimate

Model Predictions for var_estimate Objects
plot.summary.select.explore

Plot summary.select.explore Objects
summary.predictability

Summary Method for predictability Objects
summary.select.explore

Summary Method for select.explore Objects
ptsd_cor4

Data: Post-Traumatic Stress Disorder (Sample # 4)
ptsd_cor3

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

Maximum A Posteriori Precision Matrix
plot.summary.estimate

Plot summary.estimate Objects
prior_belief_var

Prior Belief Graphical VAR
plot.summary.var_estimate

Plot summary.var_estimate Objects
plot.select

Network Plot for select Objects
plot_prior

Plot: Prior Distribution
summary.var_estimate

Summary Method for var_estimate Objects
select

S3 select method
tas

Data: Toronto Alexithymia Scale (TAS)
rsa

Data: Resilience Scale of Adults (RSA)
select.estimate

Graph Selection for estimate Objects
ptsd

Data: Post-Traumatic Stress Disorder
print.BGGM

Print method for BGGM objects
summary.explore

Summary Method for explore.default Objects
summary.estimate

Summary method for estimate.default objects
prior_belief_ggm

Prior Belief Gaussian Graphical Model
select.explore

Graph selection for explore Objects
select.var_estimate

Graph Selection for var.estimate Object
summary.coef

Summarize coef Objects
select.ggm_compare_estimate

Graph Selection for ggm_compare_estimate Objects
summary.ggm_compare_estimate

Summary method for ggm_compare_estimate objects
select.ggm_compare_explore

Graph selection for ggm_compare_explore Objects
var_estimate

VAR: Estimation
weighted_adj_mat

Extract the Weighted Adjacency Matrix
summary.ggm_compare_explore

Summary Method for ggm_compare_explore Objects
women_math

Data: Women and Mathematics
zero_order_cors

Zero-Order Correlations
constrained_posterior

Constrained Posterior Distribution
Sachs

Data: Sachs Network
coef.explore

Compute Regression Parameters for explore Objects
bggm_missing

GGM: Missing Data
confirm

GGM: Confirmatory Hypothesis Testing
coef.estimate

Compute Regression Parameters for estimate Objects
bma_posterior

Compute Posterior Distributions from Graph Search Results
fisher_z_to_r

Fisher Z Back Transformation
explore

GGM: Exploratory Hypothesis Testing
fisher_r_to_z

Fisher Z Transformation
convergence

MCMC Convergence
gen_net

Simulate a Partial Correlation Matrix
estimate

GGM: Estimation
gen_ordinal

Generate Ordinal and Binary data
BGGM-package

BGGM: Bayesian Gaussian Graphical Models
asd_ocd

Data: Autism and Obssesive Compulsive Disorder
bfi

Data: 25 Personality items representing 5 factors
depression_anxiety_t1

Data: Depression and Anxiety (Time 1)
csws

Data: Contingencies of Self-Worth Scale (CSWS)