Nothing
BootAfterBoot.PI <-
function(x,p,h,nboot,prob)
{
set.seed(12345)
n <- nrow(x)
B <- OLS.AR(x,p,h,prob)
BBC <- Bootstrap(x,p,h,200)
BBCB <- BootstrapB(x,p,h,200)
bb <- BBCB$coef
eb <- sqrt( (n-p) / ( (n-p)-length(bb)))*BBCB$resid
bias <- B$coef - BBC$coef
ef <- sqrt( (n-p) / ( (n-p)-length(bb)))*BBC$resid
fore <- matrix(NA,nrow=nboot,ncol=h)
for(i in 1:nboot)
{
index <- as.integer(runif(n-p, min=1, max=nrow(eb)))
es <- eb[index,1]
xs <- ysb(x, bb, es)
bs <- LSM(xs,p)$coef
bsc <- bs-bias
bsc <- adjust(bs,bsc,p)
if(sum(bsc) != sum(bs))
bsc[p+1] <- mean(xs)*(1-sum(bsc[1:p]))
fore[i,] <- AR.ForeB(xs,bsc,h,ef,length(bs)-1)
}
Interval <- matrix(NA,nrow=h,ncol=length(prob),dimnames=list(1:h,prob))
for( i in 1:h)
Interval[i,] <- quantile(fore[,i],probs=prob)
return(list(PI=Interval,forecast=BBC$forecast))
}
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