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BGGM (version 2.0.4)

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

4,603

Version

2.0.4

License

GPL-2

Maintainer

Donald Williams

Last Published

August 20th, 2021

Functions in BGGM (2.0.4)

MCMC Convergence

GGM: Confirmatory Hypothesis Testing

Data: Sachs Network

constrained_posterior

Constrained Posterior Distribution

Compute Regression Parameters for explore Objects

BGGM: Bayesian Gaussian Graphical Models

Data: Autism and Obssesive Compulsive Disorder

Data: 25 Personality items representing 5 factors

Fisher Z Transformation

Data: Contingencies of Self-Worth Scale (CSWS)

GGM: Missing Data

Compute Regression Parameters for estimate Objects

depression_anxiety_t1

Data: Depression and Anxiety (Time 1)

Data: Interpersonal Reactivity Index (IRI)

ggm_compare_estimate

GGM Compare: Estimate

ggm_compare_confirm

GGM Compare: Confirmatory Hypothesis Testing

Obtain Imputed Datasets

depression_anxiety_t2

Data: Depression and Anxiety (Time 2)

GGM: Exploratory Hypothesis Testing

Extract the Partial Correlation Matrix

Maximum A Posteriori Precision Matrix

Data: ifit Intensive Longitudinal Data

Data: 1994 General Social Survey

plot.summary.ggm_compare_estimate

Plot summary.ggm_compare_estimate Objects

Fisher Z Back Transformation

Generate Ordinal and Binary data

plot.roll_your_own

Plot roll_your_own Objects

plot.ggm_compare_ppc

Plot ggm_compare_ppc Objects

posterior_samples

Extract Posterior Samples

Plot confirm objects

ggm_compare_explore

GGM Compare: Exploratory Hypothesis Testing

ggm_compare_ppc

GGM Compare: Posterior Predictive Check

plot.summary.estimate

Plot summary.estimate Objects

Network Plot for select Objects

plot.summary.select.explore

Plot summary.select.explore Objects

predicted_probability

Predicted Probabilities

plot.summary.var_estimate

Plot summary.var_estimate Objects

plot.summary.explore

Plot summary.explore Objects

Partial Correlation Sum

Plot pcor_sum Object

plot.predictability

Plot predictability Objects

Compute Correlations from the Partial Correlations

GGM: Estimation

Precision Matrix Posterior Distribution

Compute Custom Network Statistics

predict.explore

Model Predictions for explore Objects

predict.estimate

Model Predictions for estimate Objects

Data: Resilience Scale of Adults (RSA)

Graph selection for explore Objects

predict.var_estimate

Model Predictions for var_estimate Objects

Plot: Prior Distribution

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

posterior_predict

Posterior Predictive Distribution

Data: Post-Traumatic Stress Disorder

Print method for BGGM objects

summary.select.explore

Summary Method for select.explore Objects

select.ggm_compare_estimate

Graph Selection for ggm_compare_estimate Objects

summary.var_estimate

Summary Method for var_estimate Objects

Predictability: Bayesian Variance Explained (R2)

summary.ggm_compare_estimate

Summary method for ggm_compare_estimate objects

summary.ggm_compare_explore

Summary Method for ggm_compare_explore Objects

summary.explore

Summary Method for explore.default Objects

plot.summary.ggm_compare_explore

Plot summary.ggm_compare_explore Objects

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

weighted_adj_mat

Extract the Weighted Adjacency Matrix

S3 select method

select.estimate

Graph Selection for estimate Objects

regression_summary

Summarary Method for Multivariate or Univarate Regression

Data: Women and Mathematics

summary.estimate

Summary method for estimate.default objects

Summarize coef Objects

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

VAR: Estimation

summary.predictability

Summary Method for predictability Objects

Data: Toronto Alexithymia Scale (TAS)

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

select.var_estimate

Graph Selection for var.estimate Object

select.ggm_compare_explore

Graph selection for ggm_compare_explore Objects

zero_order_cors

Zero-Order Correlations