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Introduction to simulation input modeling

机译:模拟输入建模简介

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In this tutorial we first review introductory techniques for simulation input modeling. We then identify situations in which the standard input models fail to adequately represent the available input data. In particular, we consider the cases where the input process may (i) have marginal characteristics that are not captured by standard distributions; (ii) exhibit dependence; and (iii) change over time. For case (i), we review flexible distribution systems, while we review two widely used multivariate input models for case (ii). Finally, we review nonhomogeneous Poisson processes for the last case. We focus our discussion around continuous random variables; however, when appropriate references are provided for discrete random variables. Detailed examples will be illustrated in the tutorial presentation.
机译:在本教程中,我们首先回顾一下模拟输入建模的入门技术。然后,我们确定标准输入模型无法充分表示可用输入数据的情况。特别是,我们考虑输入过程可能(i)具有标准分布无法捕获的边际特征的情况; (ii)表现出依赖性; (iii)随时间而改变。对于情况(i),我们审查了灵活的分配系统,而对于情况(ii),我们审查了两个广泛使用的多元输入模型。最后,我们回顾了最后一种情况的非均匀泊松过程。我们将讨论的重点放在连续随机变量上。但是,当为离散随机变量提供适当的参考时。详细的示例将在教程演示中进行说明。

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