Abstract
In this talk we will summarize the main ideas and results on randomized quasi-Monte Carlo (RQMC) methods, discuss their practical aspects, and give several examples. RQMC methods provide unbiased estimators of a mathematical expectation whose variance sometimes converge at a faster rate than with standard Monte Carlo, as a function of the number of simulation runs. We will also discuss an RQMC variant specially designed for the simulation of Markov chains.
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