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Empirical likelihood inference for partial functional linear model with missing responses

机译:缺失响应的部分函数线性模型的经验似然推断

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C In this paper, we consider the empirical likelihood inferences of the partial functional linear model with missing responses. Two empirical log-likelihood ratios of the parameters of interest are constructed, and the corresponding maximum empirical likelihood estimators of parameters are derived. Under some regularity conditions, we show that the proposed two empirical log-likelihood ratios are asymptotic standard Chi-squared. Thus, the asymptotic results can be used to construct the confidence intervals/regions for the parameters of interest. We also establish the asymptotic distribution theory of corresponding maximum empirical likelihood estimators. A simulation study indicates that the proposed methods are comparable in terms of coverage probabilities and average lengths of confidence intervals. An example of real data is also used to illustrate our proposed methods.
机译:C在本文中,我们考虑了带有缺失响应的部分功能线性模型的经验似然推断。构造了感兴趣参数的两个经验对数似然比,并推导了相应的参数最大经验似然估计。在某些规律性条件下,我们表明,提出的两个经验对数似然比是渐近标准卡方。因此,渐近结果可用于构造感兴趣参数的置信区间/区域。我们还建立了相应的最大经验似然估计量的渐近分布理论。仿真研究表明,所提出的方法在覆盖概率和置信区间的平均长度方面具有可比性。实际数据的示例也用于说明我们提出的方法。

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