多标准数据的模拟

IF 2.3 Q3 MANAGEMENT
Jairo Cugliari , Antoine Rolland
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引用次数: 2

摘要

由于MCDA方法的基准测试等几个原因,MCDA社区应该对基于真实数据集的模拟多标准数据集的产生感兴趣。我们在本文中的目标是提出几种方法来模拟现有数据集中的这些新的多标准数据。模拟数据应尽可能与初始数据集相似,包括捕获初始数据集(如果有的话)中的特定结构。我们建议在此研究独立样本,基于pca的样本和基于copula的样本,并确定哪一个最成功地按需生成新数据。基于copula的方法似乎是重现标准之间特定联系的最佳方法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulation of multicriteria data

For several reasons like benchmarking of MCDA methods, the MCDA community should be interested in the production of simulated multicriteria datasets based on real datasets. Our goal in this paper is to propose several methods to simulate these new multicriteria data from an existing dataset. Simulated data should be as similar as possible to the initial dataset, including the capture of specific structure in the initial dataset (if any). We propose here to study independent sample, PCA-based sample and copula-based sample and to determine which one best succeeds in generating new data on demand. The copula-based method seems the best one to reproduce specific links between criteria.n

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来源期刊
CiteScore
2.70
自引率
10.00%
发文量
15
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