Beyond simplified pair-copula constructions
Beyond simplified pair-copula constructions
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DOI：
10.1016/j.jmva.2012.02.001
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发表时间：
2012-09-01
影响因子：
1.6
通讯作者：
Neslehova, Johanna
中科院分区：
文献类型：
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作者：
Acar, Elif F.;Genest, Christian;Neslehova, Johanna
对Copula结构（PCC）在建模多变量相关性方面提供了很大的灵活性。然而，出于推理的目的，条件对Copula通常被假设为仅通过条件裕度间接依赖于条件变量。作者在这里表明，这种假设可能是误导性的。为了评估其在三变量PCC中的有效性，他们提出了一种基于条件Copula参数的局部似然估计的可视化工具，该估计不依赖于简化假设。他们建立了估计的一致性，并通过Monte Carlo模拟评估其在有限样本中的性能。它们还提供了真实的数据应用程序。(C)2012 Elsevier Inc. All rights reserved.
Pair-copula constructions (PCCs) offer great flexibility in modeling multivariate dependence. For inference purposes, however, conditional pair-copulas are often assumed to depend on the conditioning variables only indirectly through the conditional margins. The authors show here that this assumption can be misleading. To assess its validity in trivariate PCCs, they propose a visual tool based on a local likelihood estimator of the conditional copula parameter which does not rely on the simplifying assumption. They establish the consistency of the estimator and assess its performance in finite samples via Monte Carlo simulations. They also provide a real data application. (C) 2012 Elsevier Inc. All rights reserved.