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首页> 外文期刊>Communications in Statistics >The Empirical Likelihood Inference of a Regression Parameter in Censored Partial Linear Models Based on a Piecewise Polynomial
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The Empirical Likelihood Inference of a Regression Parameter in Censored Partial Linear Models Based on a Piecewise Polynomial

机译：基于分段多项式的截面部分线性模型中回归参数的经验似然推断

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摘要

This article aims at making an empirical likelihood inference of regression parameter in partial linear model when the response variable is right censored randomly. The present studies are mainly designed to use empirical likelihood (EL) method based on synthetic dependent data, and the result cannot be applied directly due to the unknown weights in it. In this paper, we introduce a censored empirical log-likelihood ratio and demonstrate that its limiting distribution is a standard chi-square distribution. The estimating procedure of beta is developed based on piecewise polynomial method. As a result, the p-value of test and the confidence interval can be obtained without estimating other quantities. Some simulation studies are conducted to highlight the performance of the proposed EL method, and the results show a good performance. Finally, we apply our method into the real example of multiple myeloma data and show the proof of theorem.
机译：本文旨在在响应变量随机审查时对部分线性模型进行了经验似然推论。本研究主要旨在使用基于合成依赖数据的经验似然（EL）方法，并且由于其未知的重量，结果不能直接应用。在本文中，我们介绍了截取的经验日志似然比，并证明其限制分布是标准的Chi-Square分布。基于分段多项式方法开发了β的估计程序。结果，可以获得测试的p值和置信区间而无需估计其他数量。进行了一些模拟研究以突出提出的EL方法的性能，结果表现出良好的性能。最后，我们将我们的方法应用于多个骨髓瘤数据的真实例子，并显示定理证明。

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