Design and analysis of efficient quasi-Monte Carlo sampling methods

高效准蒙特卡罗采样方法的设计与分析

• 批准号: RGPIN-2015-04813
• 负责人: Lemieux, Christiane
• 金额: $ 1.24万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=635661
• 关键词: Design; analysis; efficient; quasi; Monte

In a large number of scientific disciplines, stochastic models are used to represent systems for which certain quantities of interest must be evaluated. For example, a production manager might need to compare different inventory policies in terms of their expected cost, assuming that supply and demand are both subjected to some form of randomness, or a telecommunication network designer might want to compare different designs based on their ability to handle large stochastic flows of information without incurring losses or slow-downs. The Monte Carlo method can be used to answer questions of that nature for complex systems which feature several random interacting components. This method uses random sampling in order to "simulate" possible scenarios for the system under study, and for each, the corresponding value of the quantity of interest is evaluated. By repeating this process several times, a sample of possible values for this quantity is created, which can then be used for inference, e.g., the sample mean can be used as an estimator for the quantity of interest.

在许多科学学科中，随机模型用于表示必须评估某些感兴趣数量的系统，例如，假设供应和需求，生产经理可能需要根据其预期成本来比较不同的库存策略。都受到某种形式的随机性的影响，或者电信网络设计人员可能希望根据其处理大量随机信息流而不会造成损失或速度下降的能力来比较不同的设计。蒙特卡罗方法可用于回答以下问题：复杂系统的本质该方法使用随机采样来“模拟”所研究系统的可能场景，并通过多次重复此过程来评估每个感兴趣量的相应值。创建该数量的可能值，然后可以将其用于推理，例如，样本均值可以用作感兴趣数量的估计量。