Dear all: First we run simulation through normal distribution, like p(x)=1/b, b is length of sample length, the properties of simulation we got f(x) has an unknow distribution. Through kernel density estimation we could get f(x)'s approximate distribution. Now I have run simulation through importance sampling,sampling distribution is q(x). The data (g(x))we got have a importance weight(w (x)=p(x)/q(x), p(x) is our initial sample distribution, q(x) is sampling distribution). The problems is, how to get same approximate distribution of f(x) again? Thanks for your attention
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