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BGGM (version 2.1.1)

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

12,621

Version

2.1.1

License

GPL-2

Maintainer

Philippe Rast

Last Published

February 23rd, 2024

Functions in BGGM (2.1.1)

Data: Autism and Obssesive Compulsive Disorder

GGM: Missing Data

MCMC Convergence

BGGM: Bayesian Gaussian Graphical Models

Compute Regression Parameters for estimate Objects

constrained_posterior

Constrained Posterior Distribution

Compute Regression Parameters for explore Objects

GGM: Confirmatory Hypothesis Testing

Data: Sachs Network

Data: 25 Personality items representing 5 factors

Data: Contingencies of Self-Worth Scale (CSWS)

Fisher Z Transformation

ggm_compare_confirm

GGM Compare: Confirmatory Hypothesis Testing

Simulate a Partial Correlation Matrix

depression_anxiety_t1

Data: Depression and Anxiety (Time 1)

Fisher Z Back Transformation

Generate Ordinal and Binary data

GGM: Estimation

GGM: Exploratory Hypothesis Testing

depression_anxiety_t2

Data: Depression and Anxiety (Time 2)

Data: ifit Intensive Longitudinal Data

ggm_compare_estimate

GGM Compare: Estimate

Partial Correlation Sum

Obtain Imputed Datasets

ggm_compare_explore

GGM Compare: Exploratory Hypothesis Testing

Data: 1994 General Social Survey

Maximum A Posteriori Precision Matrix

Extract the Partial Correlation Matrix

ggm_compare_ppc

GGM Compare: Posterior Predictive Check

Data: Interpersonal Reactivity Index (IRI)

Compute Correlations from the Partial Correlations

Plot pcor_sum Object

Network Plot for select Objects

plot.summary.ggm_compare_estimate

Plot summary.ggm_compare_estimate Objects

plot.summary.estimate

Plot summary.estimate Objects

plot.summary.explore

Plot summary.explore Objects

Plot confirm objects

plot.ggm_compare_ppc

Plot ggm_compare_ppc Objects

plot.predictability

Plot predictability Objects

plot.roll_your_own

Plot roll_your_own Objects

plot.summary.var_estimate

Plot summary.var_estimate Objects

predict.explore

Model Predictions for explore Objects

posterior_samples

Extract Posterior Samples

Plot: Prior Distribution

predict.estimate

Model Predictions for estimate Objects

Precision Matrix Posterior Distribution

posterior_predict

Posterior Predictive Distribution

predict.var_estimate

Model Predictions for var_estimate Objects

Predictability: Bayesian Variance Explained (R2)

predicted_probability

Predicted Probabilities

plot.summary.select.explore

Plot summary.select.explore Objects

plot.summary.ggm_compare_explore

Plot summary.ggm_compare_explore Objects

prior_belief_ggm

Prior Belief Gaussian Graphical Model

Print method for BGGM objects

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

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

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

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

prior_belief_var

Prior Belief Graphical VAR

Data: Post-Traumatic Stress Disorder

regression_summary

Summarary Method for Multivariate or Univarate Regression

Compute Custom Network Statistics

Summarize coef Objects

select.var_estimate

Graph Selection for var.estimate Object

Data: Toronto Alexithymia Scale (TAS)

select.ggm_compare_estimate

Graph Selection for ggm_compare_estimate Objects

VAR: Estimation

summary.predictability

Summary Method for predictability Objects

summary.var_estimate

Summary Method for var_estimate Objects

select.ggm_compare_explore

Graph selection for ggm_compare_explore Objects

Graph selection for explore Objects

weighted_adj_mat

Extract the Weighted Adjacency Matrix

select.estimate

Graph Selection for estimate Objects

zero_order_cors

Zero-Order Correlations

Data: Women and Mathematics

summary.select.explore

Summary Method for select.explore Objects

summary.explore

Summary Method for explore.default Objects

summary.estimate

Summary method for estimate.default objects

summary.ggm_compare_explore

Summary Method for ggm_compare_explore Objects

Data: Resilience Scale of Adults (RSA)

S3 select method

summary.ggm_compare_estimate

Summary method for ggm_compare_estimate objects