Linear regression analysis with inequality constraints on the regression parameters via empirical likelihood

Linear regression analysis with inequality constraints on the regression parameters via empirical likelihood
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通过经验似然对回归参数进行不等式约束的线性回归分析

DOI:
10.1080/00949655.2014.902459
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发表时间:
2015-06
影响因子:
1.2
通讯作者:
Wen Yu
Wen Yu
中科院分区:
数学4区
文献类型:
--
作者:
Ming Zheng;Wen Yu

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提出了一种检验线性回归分析中回归参数是否受不等式约束的经验似然比检验方法。该方法不需要对随机误差进行参数化建模和同分布假设。零假设下的检验统计量的渐近分布是卡方型的。本文还简要讨论了相邻方案下的渐近幂。此外,调整后的经验似然方法,以改善小样本量的行为,建议的测试。几个模拟研究进行了评估有限样本性能的建议测试。结果表明,所提出的测试可能是有价值的提高推理效率。一个现实生活中的例子进行了讨论,以说明理论结果。
An empirical likelihood ratio test is developed for testing for or against inequality constraints on regression parameters in linear regression analysis. The proposed approach imposes no parametric model nor identically distributing assumption on the random errors. The asymptotic distribution of the proposed test statistic under null hypothesis is shown to be of chi-bar-squared type. The asymptotic power under contiguous alternatives is also briefly discussed. Moreover, an adjusted empirical likelihood method is adopted to improve the small sample size behaviour of the proposed test. Several simulation studies are carried out to assess the finite sample performance of the proposed tests. The results reveal that the proposed tests could be valuable for improving inference efficiency. A real-life example is discussed to illustrate the theoretical results.
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