Effective estimation algorithm for parameters of multivariate Farlie-Gumbel-Morgenstern copula
Effective estimation algorithm for parameters of multivariate Farlie-Gumbel-Morgenstern copula
复制标题
多元Farlie-Gumbel-Morgenstern copula参数的有效估计算法
DOI：
10.1007/s42081-021-00118-y
复制
发表时间：
2021
影响因子：
1.3
通讯作者：
Kimura Mitsuhiro
中科院分区：
文献类型：
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作者：
Ota Shuhei;Kimura Mitsuhiro
本文主要研究了d维Farlie-Gumbel-Morgenstern（FGM）copula（）的参数估计问题，由于FGM copula（）具有依赖性参数，因此从计算复杂度的角度来看，极大似然估计对于大的fGM copula（）是不实用的。此外，随着数据的增大，函数梯度连接函数的参数约束也变得越来越复杂，这给参数估计带来了困难。在参数约束下，利用边缘推断函数的方法，提出了一种有效的d-变量FGM copula估计算法。然后，我们讨论了它的渐近正态性，以及通过模拟研究确定其性能。将该方法应用于轴承可靠性的真实的数据分析。
This paper focuses on the parameter estimation for thed-variate Farlie–Gumbel–Morgenstern (FGM) copula (), which hasdependence parameters to be estimated; therefore, maximum likelihood estimation is not practical for a largedfrom the viewpoint of computational complexity. Besides, the restriction for the FGM copula’s parameters becomes increasingly complex asdbecomes large, which makes parameter estimation difficult. We propose an effective estimation algorithm for thed-variate FGM copula by using the method of inference functions for margins under the restriction of the parameters. We then discuss its asymptotic normality as well as its performance determined through simulation studies. The proposed method is also applied to real data analysis of bearing reliability.