BayesRegularizedWishart: Regularized Wishart Estimator.

In SachaEpskamp/BayesGGM: Bayesian Estimators for Gaussian Graphical Models

Description

BayesRegularizedWishart Provides a ridge type regularized precision matrix estimate using an eigenvalue and eigenvector decomposition of the sample covariance matrix.

Usage

BayesRegularizedWishart(data, adaptive = FALSE, adfact = 2)

Arguments

data	A data matrix with rows representinh participants and columns representing variables/nodes.
adaptive	If 'TRUE' chose the amount of shrinkage based on the ration of n to p.
adfact	the ration between the two shrinkage hyper-parameters used.

Value

Returns dataframes for the precision matrix, partial correlations, and an overview of the edges fixed to 0 with estimates from each iteration of the Gibbs-sampler.

SachaEpskamp/BayesGGM documentation built on May 8, 2019, 6:44 p.m.