All functions

bfi

Data: 25 Personality items representing 5 factors

boot_eip()

Bootstrapped Edge Inclusion 'Probabilities'

coef(<ggmncv>)

Regression Coefficients from ggmncv Objects

compare_edges()

Compare Edges Between Gaussian Graphical Models

confirm_edges()

Confirm Edges

constrained() mle_known_graph()

Precision Matrix with Known Graph

desparsify()

De-Sparsified Graphical Lasso Estimator

gen_net()

Simulate a Partial Correlation Matrix

get_graph()

Extract Graph from ggmncv Objects

GGMncv-package

GGMncv: Gaussian Graphical Models with Nonconvex Regularization

ggmncv()

GGMncv

head(<eip>)

Print the Head of eip Objects

inference() significance_test()

Statistical Inference for Regularized Gaussian Graphical Models

kl_mvn()

Kullback-Leibler Divergence

ledoit_wolf()

Ledoit and Wolf Shrinkage Estimator

nct()

Network Comparison Test

penalty_derivative()

Penalty Derivative

penalty_function()

Penalty Function

plot(<eip>)

Plot Edge Inclusion 'Probabilities'

plot(<ggmncv>)

Plot ggmncv Objects

plot(<graph>)

Network Plot for select Objects

plot(<penalty_derivative>)

Plot penalty_derivative Objects

plot(<penalty_function>)

Plot penalty_function Objects

predict(<ggmncv>)

Predict method for ggmncv Objects

print(<eip>)

Print eip Objects

print(<ggmncv>)

Print ggmncv Objects

print(<nct>)

Print nct Objects

ptsd

Data: Post-Traumatic Stress Disorder

Sachs

Data: Sachs Network

score_binary()

Binary Classification