事件间隔时间为威布尔分布时计数过程的指数加权移动平均

R. Sparks, Hossein Hazrati-Marangaloo
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引用次数: 2

摘要

有泊松计数、零膨胀泊松计数和过分散泊松计数(负二项计数)的控制图,但当事件间隔时间(TBEs)是威布尔分布时,没有关于计数过程的控制图。根据我们的经验,在应用程序中,事件间隔时间的控制分布通常是威布尔分布。当事件间隔时间为威布尔分布时,计数过程不是泊松分布,也不是负二项分布。这是文献中的一个空白,这意味着当这种情况发生时,从业者没有任何帮助。本书的这一章旨在弥补这一差距,并提供一种方法,可以帮助那些在这种情况下应用控制图的人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exponentially Weighted Moving Averages of Counting Processes When the Time between Events Is Weibull Distributed
There are control charts for Poisson counts, zero-inflated Poisson counts, and over dispersed Poisson counts (negative binomial counts) but nothing on counting processes when the time between events (TBEs) is Weibull distributed. In our experience the in-control distribution for time between events is often Weibull distributed in applications. Counting processes are not Poisson distributed or negative binomial distributed when the time between events is Weibull distributed. This is a gap in the literature meaning that there is no help for practitioners when this is the case. This book chapter is designed to close this gap and provide an approach that could be helpful to those applying control charts in such cases.
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