论文标题
多重重要性抽样方案的差异分析
Variance Analysis of Multiple Importance Sampling Schemes
论文作者
论文摘要
多重重要性采样（MIS）是一种越来越多的方法，其中几个建议密度用于近似积分，通常涉及目标概率密度函数。使用多种建议可以采用各种抽样和加权方案。然后，从业者必须选择给定的方案，即采样机制和加权功能。 Elvira等人（2019年，统计科学34，129-155）提出了差异分析，显示了在某些情况下，平衡启发式估计量相对于其他竞争方案的优越性。但是，他们的某些结果仅适用于两个建议。在本文中，我们扩展并概括了这些结果，提供了新的证据，以确定错误方案之间的差异关系。
Multiple importance sampling (MIS) is an increasingly used methodology where several proposal densities are used to approximate integrals, generally involving target probability density functions. The use of several proposals allows for a large variety of sampling and weighting schemes. Then, the practitioner must choose a given scheme, i.e., sampling mechanism and weighting function. A variance analysis has been proposed in Elvira et al (2019, Statistical Science 34, 129-155), showing the superiority of the balanced heuristic estimator with respect to other competing schemes in some scenarios. However, some of their results are valid only for two proposals. In this paper, we extend and generalize these results, providing novel proofs that allow to determine the variance relations among MIS schemes.
