EBIClvglasso: Latent variable graphical LASSO using EBIC to select optimal...

Description Usage Arguments Value Author(s) References See Also

View source: R/EBIClvglasso.R

Description

This function minimizes the Extended Bayesian Information Criterion (EBIC; Chen and Chen, 2008) to choose the lvglasso tuning parameter. See lvglasso

Usage

1
EBIClvglasso(S, n, nLatents, gamma = 0.5, nRho = 100, lambda, ...)

Arguments

S

Sample variance-covariance matrix

n

Sample Size

nLatents

Number of latent variables

gamma

EBIC hyper-parameter

nRho

Number of tuning parameters to test

lambda

The lambda argument containing factor loadings, only used for starting values!

...

Arguments sent to lvglasso

Value

The optimal result of lvglasso, with two more elements:

rho

The selected tuning parameter

ebic

The optimal EBIC

Author(s)

Sacha Epskamp <[email protected]>

References

Chen, J., & Chen, Z. (2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika, 95(3), 759-771.

See Also

lvglasso


lvnet documentation built on Nov. 19, 2018, 1:04 a.m.