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Empirical likelihood confidence regions for semi-varying coefficient models with linear process errors

机译:具有线性过程误差的半变量系数模型的经验似然置信区域

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In this paper, we apply the empirical likelihood method to semi-varying coefficient models with linear process errors, propose two empirical log-likelihood ratio statistics and show that their limiting distributions are two weighted sums of independent chi-square distributions with 1 degree of freedom. By estimating the unknown weights consistently, we not only construct the empirical likelihood confidence regions for the parametric component, but also construct the point-wise empirical likelihood confidence regions and the simultaneous empirical likelihood confidence bands for the varying-coefficient functions. Monte Carlo simulation results show that the proposed empirical likelihood confidence regions have better coverage probabilities and shorter median lengths than the normal approximation confidence regions ignoring the correlation information.
机译:在本文中,我们将经验似然方法应用于具有线性过程误差的半变量系数模型,提出了两个经验对数似然比统计数据,并表明它们的极限分布是具有1个自由度的独立卡方分布的两个加权和。 。通过一致地估计未知权重,我们不仅为参数分量构造了经验似然置信区域,而且还为变系数函数构造了逐点经验似然置信区域和同时经验似然置信带。蒙特卡罗模拟结果表明,与忽略相关信息的正常近似置信度区域相比,所提出的经验似然置信度区域具有更好的覆盖率和更短的中值长度。

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