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Asymptotic Confidence Bands for Copulas Based on the Local Linear Kernel Estimator

机译:基于局部线性核估计的Copulas渐近置信带

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In this paper, we establish asymptotically optimal simultaneous confidence bands for the copula function based on the local linear kernel estimator proposed by Chen and Huang [1]. For this, we prove under smoothness conditions on the derivatives of the copula a uniform in bandwidth law of the iterated logarithm for the maximal deviation of this estimator from its expectation. We also show that the bias term converges uniformly to zero with a precise rate. The performance of these bands is illustrated by a simulation study. An application based on pseudo-panel data is also provided for modeling the dependence structure of Senegalese households’ expense data in 2001 and 2006.
机译:在本文中,我们基于Chen和Huang [1]提出的局部线性核估计量,为copula函数建立了渐近最优同时置信带。为此,我们证明了在光滑条件下,在对数的导数上,对于该估计量与其期望值的最大偏差,迭代对数的带宽定律是一致的。我们还表明,偏差项以精确的速率均匀收敛到零。仿真研究说明了这些频段的性能。还提供了一个基于伪面板数据的应用程序,用于对塞内加尔家庭2001年和2006年支出数据的依存关系模型进行建模。

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