部分线性回归模型的加权似然推断

张赛茵,梁华

系统科学与数学 ›› 2015, Vol. 35 ›› Issue (12) : 1501-1509.

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PDF(396 KB)
系统科学与数学 ›› 2015, Vol. 35 ›› Issue (12) : 1501-1509. DOI: 10.12341/jssms12689
论文

部分线性回归模型的加权似然推断

    张赛茵 1,梁华2
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WEIGHTED LIKELIHOOD INFERENCE FOR PARTIALLY LINEAR REGRESSION MODELS

    ZHANG Saiyin1,LIANG Hua2
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摘要

针对不同来源的几组相关数据集, 研究了部分线性模型的加权似然推断问题, 给出了加权似然 估计的相合性和渐近正态性. 模拟结果表明在均方误差意义下, 加权似然得到的估计优于经典的极大似然估计, 并把新的估计方法应用到艾滋病临床试验数据分析中.

Abstract

This article studies weighted likelihood inference for partially linear models when several related data sets are available from different sources. The estimator derived from the weighted likelihood can reduce the mean squared error (MSE) of the classical maximum likelihood estimator. The improvement is illustrated numerically. The resulting estimator is shown to be consistent and asymptotically normal. A real data set from an AIDS clinical trial is also analyzed.

关键词

有效性 / 预光滑 / 半参数估计 / 加权似然.

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张赛茵 , 梁华. 部分线性回归模型的加权似然推断. 系统科学与数学, 2015, 35(12): 1501-1509. https://doi.org/10.12341/jssms12689
ZHANG Saiyin , LIANG Hua. WEIGHTED LIKELIHOOD INFERENCE FOR PARTIALLY LINEAR REGRESSION MODELS. Journal of Systems Science and Mathematical Sciences, 2015, 35(12): 1501-1509 https://doi.org/10.12341/jssms12689
中图分类号: 62G08    62G20    62J02    62F12   
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