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缺失数据下φ混合样本情形非参数回归函数的经验似然推断 被引量:2

Empirical Likelihood for Nonparametric Regression Models of φ Mixing Samples with Missing Data
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摘要 在φ混合的随机误差下,本文研究了固定设计及响应变量有缺失的非参数回归模型中回归函数的经验似然置信区间的构造.首先采用非参数回归填补法对缺失的数据进行填补,其次利用补足后得到的"完全样本"构造了非参数回归函数的经验似然比统计量,并证明了经验似然比统计量的极限分布为卡方分布,利用此结果可以构造非参数回归函数的经验似然置信区间. Under the φ mixing random errors, we make the empirical likelihood (EL) inference fornonparametric regression models with fixed designs and missing responses. Based on the ‘complete sample’ after nonparametric regression imputation, we show that the EL ratio statistic of the nonparametric regression function is asymptotically Х^2-type distributed, which is used to obtain EL-based confidence intervals for the nonparametric regression function.
出处 《应用概率统计》 CSCD 北大核心 2016年第4期331-340,共10页 Chinese Journal of Applied Probability and Statistics
基金 国家自然科学基金(11201088 11271088 11361011 11261009)资助
关键词 缺失数据 φ混合 非参数回归函数 经验似然 missing data φ mixing samples nonparametric regression function empirical likelihood
作者简介 通讯作者,E-mail:liyinghua2006@qq.com.
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