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首页> 外文期刊>International journal of general systems >Computing interval-valued statistical characteristics: what is the stumbling block for reliability applications?
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Computing interval-valued statistical characteristics: what is the stumbling block for reliability applications?

机译：计算区间值统计特征：可靠性应用的绊脚石是什么？

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摘要

The application of interval-valued statistical models is often hindered by the rapid growth in imprecision that occurs when intervals are propagated through models. Is this deficiency inherent in the models? If so, what is the underlying cause of imprecision in mathematical terms? What kind of additional information can be incorporated to make the bounds tighter? The present paper gives an account of the source of this imprecision that prevents interval-valued statistical models from being widely applied. Firstly, the mathematical approach to building interval-valued models (discrete and continuous) is delineated. Secondly, a degree of imprecision is demonstrated on some simple reliability models. Thirdly, the root mathematical cause of sizeable imprecision is elucidated and, finally, a method of making the intervals tighter is described. A number of examples are given throughout the paper.
机译：区间值统计模型的应用通常会受到不精确性的快速增长的阻碍，这种不精确性在通过模型传播区间时会发生。这些缺陷是模型固有的吗？如果是这样，从数学角度讲，不精确的根本原因是什么？可以结合什么样的附加信息来使界限更紧密？本文介绍了这种不精确性的根源，它阻止了区间值统计模型的广泛应用。首先，描述了建立区间值模型（离散和连续）的数学方法。其次，在一些简单的可靠性模型上证明了不精确度。第三，阐明了不精确度较大的根本数学原因，最后，描述了使间隔更紧密的方法。全文中给出了许多示例。

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