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首页> 外文期刊>Nordic hydrology >Sampling rainfall events: a novel approach to generate large correlated samples
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Sampling rainfall events: a novel approach to generate large correlated samples

机译：降雨事件采样：一种生成大量相关样本的新颖方法

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摘要

It is essential that the correlation between variables is considered properly when using sampling-based methods. Modeling rainfall events is of great interest because the rainfall is usually the major driving force of hydrosystems. A novel method for generating correlated samples is introduced providing that the marginal distributions of variables as well as their correlations between them are known. The basic idea of the method is to adjust the correlations between samples by rearranging the positions inside marginal samples after each marginal sample is generated according to its distribution. The group method is developed in order to facilitate an efficient generation of correlated samples of large sizes. The theoretical precision associated with the group method is derived. There is a trade off between the computational efficiency of the algorithm and the precision that can be achieved when using different numbers of groups. The method is successfully applied to two cases of rainfall sample generation problems. The effectiveness of the group method is studied. Large group numbers are recommended in practical use as the samples distribute more broadly regardless of computational efficiency.
机译：使用基于采样的方法时，必须正确考虑变量之间的相关性。对降雨事件进行建模非常有趣，因为降雨通常是水力系统的主要驱动力。引入了一种生成相关样本的新方法，前提是已知变量的边际分布及其之间的相关性。该方法的基本思想是在根据每个边缘样本的分布生成边缘样本后，通过重新排列边缘样本内部的位置来调整样本之间的相关性。开发分组方法是为了促进大尺寸相关样本的有效生成。推导了与分组法相关的理论精度。在算法的计算效率与使用不同数量的组时可以实现的精度之间需要权衡。该方法成功应用于两种降雨样本生成问题。研究了分组方法的有效性。在实际使用中，建议使用大的组数，因为无论计算效率如何，样本分布都更广泛。

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