方差计算序列的平稳性

Ongun Yucesan
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引用次数: 0

摘要

在进行可靠性观察时,更多的样本意味着可以做出具有统计代表性的预测。利用这些知识,可以对失效到达特征进行统计建模。作为许多实验的自然产物,可以识别平均值和方差图来模拟不同的事件。尽管可以用这些参数对不同的情况进行建模,但它可能无法完全概述正在开发和正在测试的产品的状况。从原始信度观测序列推导出的方差计算序列可以作为一个重要的考虑因素。有了平均值和方差图,就可以进行统计预测。然而,在相同的参数下,可能存在另一种承载产品或子部件的可靠性特性。对于这个例子,识别方差计算序列是否为平稳性,并将其纳入计算中,可以产生更准确的统计模型的可能预测。在本研究中,手边的方差计算序列显示出具有平稳性,从而产生进一步建模的可能性,并强调了这一考虑的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Stationarity of Variance Calculation Series
While making reliability observations, more samples mean one can make a statistically representative prediction. It is possible to model the failure arrival characteristics statistically using this knowledge. As a natural product of many experiments, a mean and variance figure can be identified for modelling the different occurrences. Even though the different situations can be modelled with such parameters, it may not wholly outline the condition of the product being developed and under test. The variance calculation series derived from the original reliability observation series can be an important consideration. With a mean and a variance figure, a statistical prediction can be made. However, with the very same parameters, another reliability characteristic carrying product or subcomponent may exist. For this instance, identifying whether the variance calculation series is stationarity and incorporating it in calculations can yield a possible prediction of a more accurate statistical model. In this study, the variance calculation series at hand is shown to possess a stationary character yielding further modelling possibilities and emphasizing the importance of this consideration.
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