# Random sample using KDE or bootstrapping

I have an experimental sample, size of about 1000 values​​. I need to generate a much larger sample for simulation. I can create a samples like this:

library(ks)
x<-rlnorm(1000)
y<-rkde(fhat=kde(x=x, h=hpi(x)), n=10000, positive = TRUE)#
z<-sample(x, 10000, replace = TRUE)

par(mfrow=c(3,1))
hist(x, freq=F, breaks=100,  col="red")
hist(y, freq=F, breaks=100,  col="green")
hist(z, freq=F, breaks=100,  col="blue")


What fundamental limitations when using KDE or bootstrap? How else can I create such a sample?

• Please, don't cross-post on multiple sites. – chl Apr 21 '13 at 8:30