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Empirical likelihood inference for semi-parametric varying-coefficient partially linear EV models

机译:半参数变系数部分线性EV模型的经验似然推断

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In this paper, we apply empirical likelihood method to study the semi-parametric varying-coefficient partially linear errors-in-variables models. Empirical log-likelihood ratio statistic for the unknown parameter β, which is of primary interest, is suggested. We show that the proposed statistic is asymptotically standard chi-square distribution under some suitable conditions, and hence it can be used to construct the confidence region for the parameter β. Some simulations indicate that, in terms of coverage probabilities and average lengths of the confidence intervals, the proposed method performs better than the least-squares method. We also give the maximum empirical likelihood estimator (MELE) for the unknown parameter β, and prove the MELE is asymptotically normal under some suitable conditions.
机译:在本文中,我们采用经验似然法研究半参数变系数部分线性变量误差模型。建议对主要参数未知参数β进行经验对数似然比统计。我们表明,所提出的统计量在某些合适的条件下是渐近标准卡方分布,因此可以用于构造参数β的置信区域。一些仿真表明,就覆盖概率和置信区间的平均长度而言,所提出的方法比最小二乘法具有更好的性能。我们还给出了未知参数β的最大经验似然估计(MELE),并证明了MELE在某些合适的条件下是渐近正态的。

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