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基于经验似然的广义部分线性模型推断

Empirical-Likelihood-Based Inferences for Generalized Partially Linear Models.

作者信息

Liang Hua, Qin Yongsong, Zhang Xinyu, Ruppert David

机构信息

University of Rochester.

出版信息

Scand Stat Theory Appl. 2009 Sep;36(3):433-443.

Abstract

This paper considers generalized partially linear models. We propose empirical likelihood based statistics to construct confidence regions for the parametric and nonparametric componenets. The resulting statistics are shown to be asymptotically chi-squared distributed. Finite sample performance of the proposed statistics is assessed by simulation experiments. The proposed methods are applied to a dataset from an AIDS clinical trial.

摘要

本文考虑广义部分线性模型。我们提出基于经验似然的统计量来构建参数和非参数分量的置信区域。结果表明,所得统计量渐近服从卡方分布。通过模拟实验评估了所提统计量的有限样本性能。所提方法应用于一个艾滋病临床试验数据集。

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