Package: BGGM 2.1.3

Philippe Rast

BGGM: Bayesian Gaussian Graphical Models

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) <doi:10.31234/osf.io/x8dpr>, Williams and Mulder (2019) <doi:10.31234/osf.io/ypxd8>, Williams, Rast, Pericchi, and Mulder (2019) <doi:10.31234/osf.io/yt386>.

Authors:Donald Williams [aut], Joris Mulder [aut], Philippe Rast [aut, cre]

BGGM_2.1.3.tar.gz
BGGM_2.1.3.tar.gz(r-4.5-noble)BGGM_2.1.3.tar.gz(r-4.4-noble)
BGGM_2.1.3.tgz(r-4.4-emscripten)BGGM_2.1.3.tgz(r-4.3-emscripten)
BGGM.pdf |BGGM.html
BGGM/json (API)
NEWS

# Install 'BGGM' in R:
install.packages('BGGM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/donaldrwilliams/bggm/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • Sachs - Data: Sachs Network
  • asd_ocd - Data: Autism and Obssesive Compulsive Disorder
  • bfi - Data: 25 Personality items representing 5 factors
  • csws - Data: Contingencies of Self-Worth Scale
  • depression_anxiety_t1 - Data: Depression and Anxiety
  • depression_anxiety_t2 - Data: Depression and Anxiety
  • gss - Data: 1994 General Social Survey
  • ifit - Data: ifit Intensive Longitudinal Data
  • iri - Data: Interpersonal Reactivity Index
  • ptsd - Data: Post-Traumatic Stress Disorder
  • ptsd_cor1 - Data: Post-Traumatic Stress Disorder
  • ptsd_cor2 - Data: Post-Traumatic Stress Disorder
  • ptsd_cor3 - Data: Post-Traumatic Stress Disorder
  • ptsd_cor4 - Data: Post-Traumatic Stress Disorder
  • rsa - Data: Resilience Scale of Adults
  • tas - Data: Toronto Alexithymia Scale
  • women_math - Data: Women and Mathematics

5.31 score 1 packages 103 scripts 793 downloads 2 mentions 33 exports 104 dependencies

Last updated 5 months agofrom:701b94f80a. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-linux-x86_64OKNov 03 2024

Exports:bggm_missingconfirmconstrained_posteriorconvergenceestimateexplorefisher_r_to_zfisher_z_to_rgen_netgen_ordinalggm_compare_confirmggm_compare_estimateggm_compare_exploreggm_compare_ppcimpute_datamappcor_matpcor_sumpcor_to_corplot_priorposterior_predictposterior_samplesprecisionpredictabilitypredicted_probabilityprior_belief_ggmprior_belief_varregression_summaryroll_your_ownselectvar_estimateweighted_adj_matzero_order_cors

Dependencies:bainBergmBFpackBHbootcachemclicodacolorspacecpp11crayonDEoptimRdplyrergmevaluateextraDistrfansifarverfastmapforcatsgenericsGGallyggplot2ggridgesggstatsgluegslgtablehighrhmsisobandknitrlabelinglatticelavaanlifecyclelme4lpSolveAPImagrittrMASSMatrixmatrixcalcMatrixModelsmcmcMCMCpackmemoisemgcvminqamnormtmunsellmvnfastmvtnormnetworknlmenloptrnumDerivpatchworkpbivnormpillarpkgconfigplyrpracmaprettyunitsprogresspurrrQRMquadprogquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppDistRcppEigenRcppProgressRdpackreshapeRglpkrlangrlerobustbasesandwichscalesslamsnaSparseMstatnet.commonstringistringrsurvivaltibbletidyrtidyselecttimeDatetimeSeriestrustutf8vctrsviridisLitewithrxfunyamlzoo

Controlling for Variables

Rendered fromcontrol.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2020-07-23
Started: 2020-05-31

Custom Network Comparisons

Rendered fromppc_custom.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2020-05-31
Started: 2020-05-31

Custom Network Statistics

Rendered fromnetstat_custom.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2020-05-31
Started: 2020-05-31

Graphical VAR

Rendered fromvar_model.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2020-07-23
Started: 2020-07-23

In Tandem: Confirmatory and Exploratory Testing

Rendered fromin_tandem.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2024-02-24
Started: 2020-05-31

MCMC Diagnostics

Rendered frommcmc_diagnostics.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2024-02-24
Started: 2020-05-31

Network Plots

Rendered fromnetplot.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2021-08-20
Started: 2020-05-31

Predictability: Binary, Ordinal, and Continuous

Rendered frompredictability.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2020-05-31
Started: 2020-05-31

Testing Sums

Rendered fromtest_sum.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2020-05-31
Started: 2020-05-31

Three Ways to Test the Same Hypothesis

Rendered fromhyp_3_ways.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2020-05-31
Started: 2020-05-31

Troubleshoot

Rendered frominstallation.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2024-02-24
Started: 2020-05-31

Readme and manuals

Help Manual

Help pageTopics
Data: Autism and Obssesive Compulsive Disorderasd_ocd
Data: 25 Personality items representing 5 factorsbfi
GGM: Missing Databggm_missing
Compute Regression Parameters for 'estimate' Objectscoef.estimate
Compute Regression Parameters for 'explore' Objectscoef.explore
GGM: Confirmatory Hypothesis Testingconfirm
Constrained Posterior Distributionconstrained_posterior
MCMC Convergenceconvergence
Data: Contingencies of Self-Worth Scale (CSWS)csws
Data: Depression and Anxiety (Time 1)depression_anxiety_t1
Data: Depression and Anxiety (Time 2)depression_anxiety_t2
GGM: Estimationestimate
GGM: Exploratory Hypothesis Testingexplore
Fisher Z Transformationfisher_r_to_z
Fisher Z Back Transformationfisher_z_to_r
Simulate a Partial Correlation Matrixgen_net
Generate Ordinal and Binary datagen_ordinal
GGM Compare: Confirmatory Hypothesis Testingggm_compare_confirm
GGM Compare: Estimateggm_compare_estimate
GGM Compare: Exploratory Hypothesis Testingggm_compare_explore
GGM Compare: Posterior Predictive Checkggm_compare_ppc
Data: 1994 General Social Surveygss
Data: ifit Intensive Longitudinal Dataifit
Obtain Imputed Datasetsimpute_data
Data: Interpersonal Reactivity Index (IRI)iri
Maximum A Posteriori Precision Matrixmap
Extract the Partial Correlation Matrixpcor_mat
Partial Correlation Sumpcor_sum
Compute Correlations from the Partial Correlationspcor_to_cor
Plot: Prior Distributionplot_prior
Plot 'confirm' objectsplot.confirm
Plot 'ggm_compare_ppc' Objectsplot.ggm_compare_ppc
Plot 'pcor_sum' Objectplot.pcor_sum
Plot 'predictability' Objectsplot.predictability
Plot 'roll_your_own' Objectsplot.roll_your_own
Network Plot for 'select' Objectsplot.select
Plot 'summary.estimate' Objectsplot.summary.estimate
Plot 'summary.explore' Objectsplot.summary.explore
Plot 'summary.ggm_compare_estimate' Objectsplot.summary.ggm_compare_estimate
Plot 'summary.ggm_compare_explore' Objectsplot.summary.ggm_compare_explore
Plot 'summary.select.explore' Objectsplot.summary.select.explore
Plot 'summary.var_estimate' Objectsplot.summary.var_estimate
Posterior Predictive Distributionposterior_predict
Extract Posterior Samplesposterior_samples
Precision Matrix Posterior Distributionprecision
Model Predictions for 'estimate' Objectspredict.estimate
Model Predictions for 'explore' Objectspredict.explore
Model Predictions for 'var_estimate' Objectspredict.var_estimate
Predictability: Bayesian Variance Explained (R2)predictability
Predicted Probabilitiespredicted_probability
Print method for 'BGGM' objectsprint.BGGM
Prior Belief Gaussian Graphical Modelprior_belief_ggm
Prior Belief Graphical VARprior_belief_var
Data: Post-Traumatic Stress Disorderptsd
Data: Post-Traumatic Stress Disorder (Sample # 1)ptsd_cor1
Data: Post-Traumatic Stress Disorder (Sample # 2)ptsd_cor2
Data: Post-Traumatic Stress Disorder (Sample # 3)ptsd_cor3
Data: Post-Traumatic Stress Disorder (Sample # 4)ptsd_cor4
Summarary Method for Multivariate or Univarate Regressionregression_summary
Compute Custom Network Statisticsroll_your_own
Data: Resilience Scale of Adults (RSA)rsa
Data: Sachs NetworkSachs
S3 'select' methodselect
Graph Selection for 'estimate' Objectsselect.estimate
Graph selection for 'explore' Objectsselect.explore
Graph Selection for 'ggm_compare_estimate' Objectsselect.ggm_compare_estimate
Graph selection for 'ggm_compare_explore' Objectsselect.ggm_compare_explore
Graph Selection for 'var.estimate' Objectselect.var_estimate
Summarize 'coef' Objectssummary.coef
Summary method for 'estimate.default' objectssummary.estimate
Summary Method for 'explore.default' Objectssummary.explore
Summary method for 'ggm_compare_estimate' objectssummary.ggm_compare_estimate
Summary Method for 'ggm_compare_explore' Objectssummary.ggm_compare_explore
Summary Method for 'predictability' Objectssummary.predictability
Summary Method for 'select.explore' Objectssummary.select.explore
Summary Method for 'var_estimate' Objectssummary.var_estimate
Data: Toronto Alexithymia Scale (TAS)tas
VAR: Estimationvar_estimate
Extract the Weighted Adjacency Matrixweighted_adj_mat
Data: Women and Mathematicswomen_math
Zero-Order Correlationszero_order_cors