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半函数线性模型的k近邻经验似然推断
KNN Estimation in Functional Partial Linear Model with Empirical Likelihood Method
【摘要】 将k近邻方法应用到经验似然方法中,并以此来研究函数型数据下,半函数部分线性模型的估计问题.通过构造参数分量的对数经验似然比函数,得到该经验对数似然比依分布收敛于χ~2分布,同时给出了非参数部分的估计值和收敛速度,并给出了经验似然方法在模拟研究中的应用.
【Abstract】 kNN method is used to study the estimation problem of semi-functional partial linear models under functional data with developed empirical likelihood method.The empirical log-likelihood ratios of the parameters of the model are constructed.And the proposed empirical log-likelihood ratios are asymptotic standard Chi-squared, and uniform almost-complete convergence with rates for the estimator of non-parametric part is given.Then a simulation study ia carried out to indicate the proposed methods.
【关键词】 半函数部分线性模型;
经验似然;
函数型数据;
k近邻;
【Key words】 semi-functional partial linear model; empirical likelihood; functional data; kNN method;
【Key words】 semi-functional partial linear model; empirical likelihood; functional data; kNN method;
- 【文献出处】 大学数学 ,College Mathematics , 编辑部邮箱 ,2021年03期
- 【分类号】O212.1
- 【下载频次】88