Nothing
simmix<-function(n,M,sig,p,seed,d=NULL)
{
#Simulates a mixture of l normal distributions in R^d, l>1
#with diagonal cov matrices
#n is the sample size
#M is l*d-matrix, rows are the means
#sig is l*d-matrix, for l:th mixture d covariances
#p is l-vector, proportion for each mixture
#returns n*d-matrix
if (is.null(d)) d<-dim(M)[2]
set.seed(seed)
#if (dim(M)[2]==1) d<-1 else d<-length(M[1,])
if (d==1){
data<-simmix1d(n,M,sig,p,seed)
}
else{
l<-length(M[,1])
data<-matrix(rnorm(d*n),,d) #n*d matriisi, valkoista kohinaa
for (i in 1:n){
ehto<-runif(1)
alku<-0
loppu<-p[1]
lippu<-0
for (j in 1:(l-1)){
if ((alku<=ehto) && (ehto<loppu)){
data[i,]<-sig[j,]*data[i,]+M[j,]
lippu<-1
}
alku<-alku+p[j]
loppu<-loppu+p[j+1]
}
if (lippu==0) data[i,]<-sig[l,]*data[i,]+M[l,]
}
}
return(data)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.