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Linear B-spline copulas with applications to nonparametric estimation of copulas

机译:线性B样条copulas在copula的非参数估计中的应用

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摘要

In this paper, we propose a method for constructing a new class of copulas. They are called linear B-spline copulas which are a good approximation of a given complicated copula by using finite numbers of values of this copula without the loss of some essential properties. Moreover, rigorous analysis shows that the empirical linear B-spline copulas are more effective than empirical copulas to estimate perfectly dependent copulas. For the cases of nonperfectly dependent copulas, simulations show that the empirical linear B-spline copulas also improve the empirical copulas to estimate the underlying copula structure. Furthermore, we compare the performance of parametric estimation of copulas based on the empirical copulas with that based on the empirical linear B-spline copulas by simulations. In most of the cases, the latter are better than the former.
机译:在本文中,我们提出了一种用于构造一类新的系蝇的方法。它们被称为线性B样条copula,通过使用有限数量的copula值而不损失某些基本属性,可以很好地近似给定的复杂copula。此外,严格的分析表明,经验线性B样条关联比估计经验依赖比关联更有效。对于非完全依赖的copulas,仿真显示,经验线性B样条copulas还改善了经验copulas以估计潜在的copula结构。此外,我们通过仿真比较了基于经验copulas和基于经验线性B样条copulas的copulas的参数估计性能。在大多数情况下,后者要好于前者。

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