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One-Sided Tolerance Limits in Balanced and Unbalanced One-Way Random Models Based on Generalized Confidence Intervals

机译:基于广义置信区间的平衡与不平衡单向随机模型中的单边公差极限

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摘要

We consider the problem of deriving one-sided tolerance intervals in the one-way random model with balanced as well as unbalanced data, under the usual normality assumptions. The problems investigated deal with the computation of such intervals for the observable random variable, as well as the unobservable random effect in the one-way random model. The tolerance limits are derived using the concept of a generalized confidence interval. Some approximations are derived for the tolerance limits, and their performance is investigated by simulation. The simulation results show that the proposed tolerance limits are quite satisfactory for practical use.
机译:在通常的正态性假设下,我们考虑在具有平衡和不平衡数据的单向随机模型中推导单边公差区间的问题。研究的问题涉及可观察的随机变量的此类间隔的计算以及单向随机模型中的不可观察的随机效应。公差极限是使用广义置信区间的概念得出的。推导出公差极限的一些近似值,并通过仿真研究其性能。仿真结果表明,所提出的公差极限对于实际使用是非常令人满意的。

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