In this work, we analyze the noisy importance sampling (IS), i.e., IS working with noisy evaluations of the target density. We present the general framework and derive optimal proposal densities for noisy IS estimators. The optimal proposals incorporate the information of the variance of the noisy realizations, proposing points in regions where the noise power is higher. We also compare the use of the optimal proposals with previous optimality approaches considered in a noisy IS framework.

翻译：在这项工作中,我们分析吵闹的重要抽样(IS),即对目标密度进行吵闹的评估(IS),我们提出总体框架,并为吵闹的IS估计员提出最佳建议密度。最佳建议包括噪音认知的差异信息,在噪音功率较高的区域提出点数。我们还将最佳建议的使用与以前在噪音IS框架中考虑的最佳方法进行比较。