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BGGM (version 2.1.5)

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

2.1.5

License

GPL-2

Maintainer

Philippe Rast

Last Published

December 22nd, 2024

Functions in BGGM (2.1.5)

Data: Sachs Network

Data: Autism and Obssesive Compulsive Disorder

Data: 25 Personality items representing 5 factors

GGM: Confirmatory Hypothesis Testing

constrained_posterior

Constrained Posterior Distribution

GGM: Estimation

Fisher Z Transformation

Fisher Z Back Transformation

Simulate a Partial Correlation Matrix

depression_anxiety_t1

Data: Depression and Anxiety (Time 1)

Generate Ordinal and Binary data

Data: Contingencies of Self-Worth Scale (CSWS)

MCMC Convergence

depression_anxiety_t2

Data: Depression and Anxiety (Time 2)

GGM: Exploratory Hypothesis Testing

Data: ifit Intensive Longitudinal Data

ggm_compare_explore

GGM Compare: Exploratory Hypothesis Testing

ggm_compare_estimate

GGM Compare: Estimate

ggm_compare_ppc

GGM Compare: Posterior Predictive Check

ggm_compare_confirm

GGM Compare: Confirmatory Hypothesis Testing

Obtain Imputed Datasets

Maximum A Posteriori Precision Matrix

Data: Interpersonal Reactivity Index (IRI)

plot.roll_your_own

Plot roll_your_own Objects

plot.predictability

Plot predictability Objects

Plot confirm objects

plot.summary.ggm_compare_explore

Plot summary.ggm_compare_explore Objects

plot.ggm_compare_ppc

Plot ggm_compare_ppc Objects

plot.summary.estimate

Plot summary.estimate Objects

plot.summary.explore

Plot summary.explore Objects

plot.summary.select.explore

Plot summary.select.explore Objects

Network Plot for select Objects

Compute Correlations from the Partial Correlations

Plot pcor_sum Object

plot.summary.ggm_compare_estimate

Plot summary.ggm_compare_estimate Objects

Perform Bayesian Graph Search and Optional Model Averaging

Data: 1994 General Social Survey

plot.summary.var_estimate

Plot summary.var_estimate Objects

Precision Matrix Posterior Distribution

predict.estimate

Model Predictions for estimate Objects

Extract the Partial Correlation Matrix

Plot: Prior Distribution

Partial Correlation Sum

prior_belief_ggm

Prior Belief Gaussian Graphical Model

Print method for BGGM objects

select.ggm_compare_estimate

Graph Selection for ggm_compare_estimate Objects

posterior_predict

Posterior Predictive Distribution

prior_belief_var

Prior Belief Graphical VAR

Data: Resilience Scale of Adults (RSA)

S3 select method

predict.explore

Model Predictions for explore Objects

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

summary.var_estimate

Summary Method for var_estimate Objects

select.ggm_compare_explore

Graph selection for ggm_compare_explore Objects

posterior_samples

Extract Posterior Samples

Predictability: Bayesian Variance Explained (R2)

Data: Toronto Alexithymia Scale (TAS)

predicted_probability

Predicted Probabilities

predict.var_estimate

Model Predictions for var_estimate Objects

regression_summary

Summarary Method for Multivariate or Univarate Regression

Compute Custom Network Statistics

summary.ggm_compare_estimate

Summary method for ggm_compare_estimate objects

summary.ggm_compare_explore

Summary Method for ggm_compare_explore Objects

Data: Post-Traumatic Stress Disorder

summary.estimate

Summary method for estimate.default objects

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

summary.explore

Summary Method for explore.default Objects

Data: Women and Mathematics

select.estimate

Graph Selection for estimate Objects

Graph selection for explore Objects

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

VAR: Estimation

weighted_adj_mat

Extract the Weighted Adjacency Matrix

zero_order_cors

Zero-Order Correlations

select.var_estimate

Graph Selection for var.estimate Object

Summarize coef Objects

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

summary.predictability

Summary Method for predictability Objects

summary.select.explore

Summary Method for select.explore Objects

GGM: Missing Data

Compute Regression Parameters for explore Objects

Compute Regression Parameters for estimate Objects

BGGM: Bayesian Gaussian Graphical Models

Compute Posterior Distributions from Graph Search Results