You have a couple of issues. The major one is that return
should be outside the for
loop. Also, you should define t
and zscore
as vectors, and x
as a list.
I think this will work.
Side note: t
seems unnecessary in this function. You could get away with using
zscore[i] <- skwness(x[[i]])/(6/n)
and get rid of t
all together
skwness <- function(x){
n <- length(x)
skew.stat <- (1/(n))*(1/(sd(x)^3))*(sum((x-mean(x))^3))
return(skew.stat)
}
skw <- function(n, nsims){
t <- zscore <- numeric(nsims)
x <- vector("list", nsims)
for (i in 1:nsims) {
x[[i]] <- rnorm(n)
t[i] <- skwness(x[[i]])
zscore[i] <- t[i]/(6/n)
}
return(zscore)
}
Giving it a go:
> x <- rnorm(100)
> skwness(x)
[1] 0.2332121
> skw(100, 10)
[1] 0.6643582 -1.6963196 -2.9192317 -2.7166170 4.9255001 0.0773482 3.9171435
[8] -3.3993994 -2.4258642 0.7075989