I found a proof, but can not follow. The critical part is the following:
I need an approximation / upperbound to n. The authors assert that it is in order of . Can anyone explain it?
Thanking you in anticipation!
What I'm trying to do is, estimate the bias of a self normalized importance sampler, that is
for sake of simplicity let's see it as
the bias is given bei
a taylor expansion for around the expected values X and 1 leads to the given equation above.
I'm interested in an estimation depending on n. there are some books asserting that it is
for some constant .
Can you give me a more detailed explanation?