EBICgolazo: Finds the optimal penalty parameter for Graphical Oriented...

In pzwiernik/mtp2: Working with Gaussian totally positive distributions

Description

This function computes the EBIC criterion for a seried of rho parameters. The penalty matrices are $rho L$, $rho U$, where L and U are fixed in advance.

Usage

EBICgolazo(
  S,
  n = NULL,
  L = NULL,
  U = NULL,
  tol = 1e-06,
  edge.tol = 1e-04,
  gamma = 0.5,
  rhomin = 0.01,
  rhomax = 1,
  nrhos = 50,
  output = TRUE
)

Arguments

S	the sample covariance matrix
n	the sample size
L	matrix of lower penalties (can be -Inf)
U	matrix of upper penalties (can be Inf)
tol	the convergence tolerance (default tol=1e-8)
edge.tol	which entries of K are treated as zero
gamma	the EBIC parameter between 0 and 1
rhomin	minimal rho to check
rhomax	maximal rho to check
nrhos	positive penalty (can be Inf)
output	if TRUE (default) the output will be printed.

Value

the optimal value of the concentration matrix

the number of iterations the algorithm needed to converge

the corresponding value of the log-likelihood

Examples

print(TRUE)

pzwiernik/mtp2 documentation built on Aug. 9, 2020, 12:34 p.m.