Random covariance matrix
Builds a positive definite matrix from an undirected graph G that can be used as a covariance matrix for a Gaussian graphical model with graph G. The inverse of the resulting matrix contains zeroes at the missing edges of the given undirected graph G.
undirected graph specified either as a
real number between -1/(n.var-1) and 1 corresponding to the mean marginal correlation
algorithm to employ in the matrix completion operations
employed to construct a positive definite matrix with the
zero pattern specified in
tolerance under which the matrix completion algorithm stops.
show progress on the calculations.
logical; if FALSE then the faster C implementation is used in the internal call to the HTF, or IPF, algorithm (default); if TRUE then only R code is executed.
The random covariance matrix is built by first generating a random matrix
with the function
qpRndWishart from a Wishart distribution
whose expected value is a matrix with unit diagonal and constant off-diagonal
entries equal to
A random positive definite matrix that can be used as a covariance matrix
for a Gaussian graphical model with graph
Tur, I., Roverato, A. and Castelo, R. Mapping eQTL networks with mixed graphical Markov models. Genetics, 198(4):1377-1393, 2014.
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