# NOT RUN {
if(require(mvtnorm)){
## Generate two random samples of size 50 from two multivariate normal distributions
# sample size
n<-50
# true parameters of class 1 and class 2
param.class1<-simulation$condition1
param.class2<-simulation$condition2$`5`$`2`
# simulated dataset
data.class1<-rmvnorm(n = n,mean =param.class1$mu ,sigma =param.class1$S)
data.class2<-rmvnorm(n = n,mean =param.class2$mu ,sigma=param.class2$S)
data<-rbind(data.class1,data.class2)
classes<-c(rep(1,nrow(data.class1)),rep(2,nrow(data.class2)))
## estimated parameters: maximum likelihood estimate
est.param<-parameters(data = data,classes =classes ,shrink = FALSE)
## estimated parameters: regularized estimate
est.param.shrink<-parameters(data = data,classes =classes ,shrink = TRUE)
# tuning values and other info on shrinkage estimate
str(est.param.shrink$shrink.info)
}
# }
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