不平衡单向随机效应模型中方差分量置信区间的比较

Q4 Mathematics
Arisa Jiratampradab, Thidaporn Supapakorn, J. Suntornchost
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引用次数: 0

摘要

摘要本文的目的是研究和比较不平衡单向随机效应模型中方差分量置信区间的构造方法。这些方法基于经典的精确、广义枢轴量、基准推断和基准广义枢轴量。标准的比较涉及保持在0.95的标称置信水平和置信区间的最短平均长度的经验覆盖概率。仿真结果表明,基于广义关键量和基准推理的方法在经验覆盖概率和置信区间平均长度方面都表现良好。经典精确方法在某些情况下表现良好,而基准广义关键量在非常不平衡的设计中表现良好。因此,建议在所有情况下使用基于广义关键量的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of confidence intervals for variance components in an unbalanced one-way random effects model
Abstract The purpose of this paper is to study and compare the methods for constructing confidence intervals for variance components in an unbalanced one-way random effects model. The methods are based on a classical exact, generalised pivotal quantity, a fiducial inference and a fiducial generalised pivotal quantity. The comparison of criteria involves the empirical coverage probability that maintains at the nominal confidence level of 0.95 and the shortest average length of the confidence interval. The simulation results show that the method based on the generalised pivotal quantity and the fiducial inference perform very well in terms of both the empirical coverage probability and the average length of the confidence interval. The classical exact method performs well in some situations, while the fiducial generalised pivotal quantity performs well in a very unbalanced design. Therefore, the method based on the generalised pivotal quantity is recommended for all situations.
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来源期刊
Statistics in Transition
Statistics in Transition Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.00
自引率
0.00%
发文量
0
审稿时长
9 weeks
期刊介绍: Statistics in Transition (SiT) is an international journal published jointly by the Polish Statistical Association (PTS) and the Central Statistical Office of Poland (CSO/GUS), which sponsors this publication. Launched in 1993, it was issued twice a year until 2006; since then it appears - under a slightly changed title, Statistics in Transition new series - three times a year; and after 2013 as a regular quarterly journal." The journal provides a forum for exchange of ideas and experience amongst members of international community of statisticians, data producers and users, including researchers, teachers, policy makers and the general public. Its initially dominating focus on statistical issues pertinent to transition from centrally planned to a market-oriented economy has gradually been extended to embracing statistical problems related to development and modernization of the system of public (official) statistics, in general.
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