A principled stopping rule for importance sampling

@article{Agarwal2021APS,
  title={A principled stopping rule for importance sampling},
  author={Medha Agarwal and Dootika Vats and V{\'i}ctor Elvira},
  journal={Electronic Journal of Statistics},
  year={2021}
}
Importance sampling (IS) is a Monte Carlo technique that relies on weighted samples, simulated from a proposal distribution, to estimate intractable integrals. The quality of the estimators improves with the number of samples. However, for achieving a desired quality of estimation, the required number of samples is unknown and depends on the quantity of interest, the estimator, and the chosen proposal. We present a sequential stopping rule that terminates simulation when the overall variability… 
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References

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