Nothing

```
# DESP/R/DESP_RV.R by A. S. Dalalyan and S. Balmand Copyright (C) 2015-
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License (version 3) as published by
# the Free Software Foundation.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# A copy of the GNU General Public License is available at
# http://www.r-project.org/Licenses/
#
DESP_RV <-
function(X,B,Theta=NULL) {
# estimation of the diagonal of the precision matrix by residual variance when the true value of B is known or has already been estimated
# the observations of the data matrix X are assumed to have zero mean
# read the sample size and the number of variables
D = dim(X);
n = D[1]; # n is the sample size
normE2 <- function(x){
# squared Euclidean norm of a vector
sum(x^2)
}
if(is.null(Theta))
{
Phi <- apply(tcrossprod(X,t(B)),2,normE2)/n;
}
else
{
Phi <- apply(tcrossprod(X,t(B))-Theta,2,normE2)/n;
}
return(1/Phi);
}
DESP_AD <-
function(X,B,Theta=NULL) {
# estimation of the diagonal of the precision matrix by average absolute deviation around the mean when the true value of B is known or has already been estimated
# the observations of the data matrix X are assumed to have zero mean
# read the sample size and the number of variables
D = dim(X);
n = D[1]; # n is the sample size
norm1 <- function(x){
# l1 norm of a vector
sum(abs(x))
}
if(is.null(Theta))
{
Phi <- apply(tcrossprod(X,t(B)),2,norm1)^2 * pi/2 /n^2;
}
else
{
Phi <- apply(tcrossprod(X,t(B))-Theta,2,norm1)^2 * pi/2 /n^2;
}
return(1/Phi);
}
```

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