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Empirical likelihood for heteroscedastic partially linear errors-in-variables model with α-mixing errors

机译:具有α混合误差的异方差部分线性误差变量模型的经验似然

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In this paper, we apply the empirical likelihood method to heteroscedastic partially linear errors-in-variables model. For the cases of known and unknown error variances, the two different empirical log-likelihood ratios for the parameter of interest are constructed. If the error variances are known, the empirical log-likelihood ratio is proved to be asymptotic chi-square distribution under the assumption that the errors are given by a sequence of stationary α-mixing random variables. Furthermore, if the error variances are unknown, we show that the proposed statistic is asymptotically standard chi-square distribution when the errors are independent. Simulations are carried out to assess the performance of the proposed method.
机译:在本文中,我们将经验似然方法应用于异方差部分线性变量误差模型。对于已知和未知误差方差的情况,构建感兴趣参数的两个不同的经验对数似然比。如果误差方差是已知的,则在假设误差由一系列平稳的α混合随机变量给定的假设下,经验对数似然比被证明是渐近卡方分布。此外,如果误差方差未知,则表明当误差独立时,建议的统计量是渐近标准卡方分布。仿真进行了评估所提出的方法的性能。

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