用正交投影估计联结体和联结体密度的非参数

IF 2.5 Q2 ECONOMICS

Econometrics and Statistics Pub Date : 2025-10-01 DOI:10.1016/j.ecosta.2023.04.002

Yves I. Ngounou Bakam , Denys Pommeret

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引用次数: 0

摘要

提出了一种基于Legendre正交多项式的非参数联结密度估计。然后通过积分推导出非参数共轭估计量。讨论了它们的渐近性质。这两个估计量都是基于一串矩，这些矩描述了联结的特征，我们称之为联结系数。提出了一种数据驱动的方法来选择要使用的copula系数的数量。密集的模拟研究表明，与大型竞争对手相比，copula和copula密度估计器都具有良好的性能。两个真实的数据集说明了这种方法。

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Nonparametric estimation of copulas and copula densities by orthogonal projections

A nonparametric copula density estimator based on Legendre orthogonal polynomials is proposed. A nonparametric copula estimator is then deduced by integration. Their asymptotic properties are reviewed. Both estimators are based on a sequence of moments that characterize the copulas and that we shall call the copula coefficients. A data-driven method is proposed to select the number of copula coefficients to use. An intensive simulation study shows the good performance of both copulas and copula densities estimators compared to a large panel of competitors. Two real datasets illustrate this approach.

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来源期刊

Econometrics and Statistics ECONOMICS-

CiteScore

3.10

自引率

10.50%

发文量

期刊介绍： Econometrics and Statistics is the official journal of the networks Computational and Financial Econometrics and Computational and Methodological Statistics. It publishes research papers in all aspects of econometrics and statistics and comprises of the two sections Part A: Econometrics and Part B: Statistics.