Self-normalized importance sampling
= Self-normalized importance sampling
For an unnormalized target density, self-normalized importance sampling uses weights $w_i=f(Y_i)/h(Y_i)$ and estimates expectations by $\sum_iw_ig(Y_i)/\sum_iw_i$. Resampling a point $Y_i$ with probability proportional to $w_i$ produces the associated weighted empirical distribution.