On the Error Rate of Importance Sampling with Randomized Quasi-Monte Carlo
On the Error Rate of Importance Sampling with Randomized Quasi-Monte Carlo
.Importance sampling (IS) is valuable in reducing the variance of Monte Carlo sampling for many areas, including finance, rare event simulation, and Bayesian inference. It is natural and obvious to combine quasi-Monte Carlo (QMC) methods with IS to achieve a faster rate of convergence. However, a naive replacement of Monte …