Dpmdtl: Return the result of difference of two precision matrices...
In Difdtl: Difference of Two Precision Matrices Estimation

Description Usage Arguments Value Author(s) References Examples

Calculate the result of difference of two precision matrices estimation by d-trace loss with lasso penalty, given two sample classes.

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Dpmdtl(X1, X0, lambda = NULL, nlambda = 10, lambda.min.ratio = NULL, 
rho = NULL, shrink = NULL, prec = 0.001, correlation = FALSE, 
tuning = c("none", "aic", "bic", "nbic"))

`X1`	A nXp matrix.
`X0`	A nXp matrix.
`lambda`	The tuning parameter of lasso penalty.
`nlambda`	The number of tuning parameter of lasso penalty for selection.
`lambda.min.ratio`
`rho`	The parameter in augmented Lagrange method. The rho here equals the 2*rho in the reference paper.
`shrink`
`prec`
`correlation`
`tuning`	The method used in the lambda selection.

`Dpmdtl`	The result of estimation by d-trace loss with lasso penalty.
`lambda`	The lambda used in the lasso penalty
`nlambda`	The number of lambda used in the lasso penalty
`opt`	Number of best lambda chosen by different matrix norms.

Huili Yuan

Huili Yuan, Ruibin Xi and Minghua Deng(2015). Differential Network Analysis via the Lasso Penalized D-Trace Loss. http://arxiv.org/abs/1511.09188

##generate samples
library(MASS)
set.seed(1);
Sigma1 = genp(50,0.2,0.5)
set.seed(1);
Sigma2 = Sigma1+genp1(50,100,0.5)
tdelta = Sigma2-Sigma1
SigmaX<-solve(Sigma1)
SigmaY<-solve(Sigma2)
n<-200
p<-50
X1<-mvrnorm(n,rep(0,p),SigmaX)
Y1<-mvrnorm(n,rep(0,p),SigmaY)
##use of Dpmdtl
dpmdtl<- Dpmdtl(X1,Y1,nlambda=10,tuning="bic")