Nothing
Wgenerate <-
function(alpha,
sigma=1,
eta,
samplesize=0,
X,
Z,
seed1=0,
seed2=0){
if(samplesize==0&is.null(X)&is.null(Z))
stop("data is empty")
if(is.null(alpha)|is.null(eta))
stop("coeffiencts can't be empty")
#the size of sample
if(samplesize==0){
if(!is.null(X))
samplesize <- dim(X)[1]
else
samplesize <- dim(Z)[1]
}
#class size
classsize <- dim(alpha)[2]
if(classsize!=dim(eta)[2])
stop("the class size is vague")
alphasize <- dim(alpha)[1]
etasize <- dim(eta)[1]
#generate X and Z if they aren't exists
set.seed(seed1)
if(is.null(X))
X <- matrix(rnorm(samplesize*alphasize,0,1),samplesize,alphasize)
if(is.null(Z))
Z <- matrix(rnorm(samplesize*etasize,0,1),samplesize,etasize)
#calculate the mean value of each class
mu <- Z%*%alpha#dim=samplesize*alphasize
#simulation the distribution
Ytemp <- matrix(rnorm(samplesize*classsize,0,1),samplesize,classsize)
Ytemp <- Ytemp*sigma+mu
#generate G and Y
G <- Ggenerate(eta,X,seed2)
Y <- matrix(apply(Ytemp*G,1,sum),samplesize,1)
return(list(X=X,Z=Z,Y=Y,G=G))
}
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