Construct GGM prior parameters — ggm

Takes the inputs for a Gaussian graphical model and bundles them into one object, ready for prior elicitation with elicit_prior.

Usage

ggm_parameters(K, G, nu, mu = NULL, pip = NULL)

K: A p by p symmetric positive-definite precision matrix, .
G: A p by p symmetric 0/1 adjacency matrix with zero diagonal.
nu: Prior study size (degrees of freedom).
mu: Mean vector of length p. The default NULL corresponds to the centered (zero-mean) case that all current methods assume. Supplying a non-NULL mu is not yet supported.
pip: Prior inclusion probabilities. The default NULL corresponds to the uniform prior. Can be a single probability or a p by p symmetric matrix with zero diagonal.

A ggm_parameters object, which also inherits from bgm_parameters.