jewel_inner {jewel} | R Documentation |
Estimate Gaussian graphical models from multiple datasets
Description
This function estimates Gaussian graphical models (i.e. networks of conditional dependencies, direct connections between variables) given several datasets. We assume that datasets contain measurements of the same variables collected under different conditions (different equipment, locations, even sub-types of disease).
Usage
jewel_inner(
X,
lambda1,
lambda2 = NULL,
Theta = NULL,
W = NULL,
tol = 0.01,
maxIter = 10000,
verbose = TRUE
)
Arguments
X |
a list of |
lambda1 |
a number, first regularization parameter (of the common penalty). |
lambda2 |
an optional number, second regularization parameter (of the class-specific penalty). If NULL, set to |
Theta |
an optional list of |
W |
an optional list of |
tol |
an optional number, convergence threshold controlling the relative error between iterations. The default value is 0.01. |
maxIter |
an optional number, maximum allowed number of iterations. The default value is 10 000. |
verbose |
if verbose = FALSE, tracing information printing is disabled. The default value is TRUE. |
Value
The following list is returned
-
CommonG
- an adjacency matrix of the common estimated graph (intersection ofK
estimated graphs). -
G_list
- a list ofK
adjacency matrices for each estimated graph. -
Theta
- a list ofK
estimated covariance matrices. -
BIC
– a number, value of Bayesian information criterion for resulting graphs.