Drawbacks of Quasi-Monte Carlo
Lemieux mentioned the drawbacks of quasi-Monte Carlo in.
- In order for to be smaller than, needs to be small and needs to be large.
- For many functions arising in practice, .
- We only know an upper bound on the error(i.e., ε ≤ V(f) DN) and it is difficult to compute and .
In order to overcome these difficulties, we can use a randomized quasi-Monte Carlo method.
Read more about this topic: Quasi-Monte Carlo Method
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