R/r.FGSCN.R

In a-mahdavi/SSMFGSN.EM: EM algorithms for the SSMFGSN distributions

r.FGSCN <- function(n , xi, s, la, nu1, nu2){
		m <- length(la) ; a=seq(1,2*m-1,by=2)
		y <- 0
		for(i in 1:n){
		x0 <- rnorm(1)
		tau <- sample(c(nu2,1),size=1,prob=c(nu1,(1-nu1)))
		x0 <- tau^(-1/2)*x0
		a.x0 <- t(outer(x0,a,'^'))
		x1<- rnorm(1)
		if( x1 < as.numeric(t(la)%*%a.x0) )
		y[i] <- x0
		else
		y[i] <- -x0
		}
		return(xi + s*y)
		}