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Empirical likelihood for high-dimensional partially functional linear model
Random Matrices: Theory and Applications ( IF 0.9 ) Pub Date : 2019-08-05 , DOI: 10.1142/s2010326320500173
Zhiqiang Jiang 1 , Zhensheng Huang 1 , Guoliang Fan 2
Affiliation  

This paper considers empirical likelihood inference for a high-dimensional partially functional linear model. An empirical log-likelihood ratio statistic is constructed for the regression coefficients of non-functional predictors and proved to be asymptotically normally distributed under some regularity conditions. Moreover, maximum empirical likelihood estimators of the regression coefficients of non-functional predictors are proposed and their asymptotic properties are obtained. Simulation studies are conducted to demonstrate the performance of the proposed procedure and a real data set is analyzed for illustration.

中文翻译:

高维部分函数线性模型的经验似然

本文考虑了高维部分函数线性模型的经验似然推断。为非功能性预测变量的回归系数构建了一个经验对数似然比统计量,并证明在某些规律性条件下呈渐近正态分布。此外,提出了非功能预测器回归系数的最大经验似然估计量,并获得了它们的渐近特性。进行模拟研究以证明所提出程序的性能,并分析真实数据集以进行说明。
更新日期:2019-08-05
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