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Average Run Lengths for CUSUM Schemes When Observations Are Exponentially Distributed

Authors: Stephen Vardeman; Di-ou Ray;

Average Run Lengths for CUSUM Schemes When Observations Are Exponentially Distributed

Abstract

Page (1954) originally noted that it is possible to find an integral equation whose solution gives average run lengths for one-sided CUSUM schemes. Lucas and Crosier (1982), for the case of normally distributed observations, have obtained numerical solutions to Page's integral equation and used these in their study of so called fast-initial-response CUSUM charts. In this article we show that for the case of exponentially distributed observations, the Page equation can be solved without resorting to approximations. We then provide some tables of average run lengths for the exponential case and comment on an application of exponential CUSUM charts to controlling the intensity of a Poisson process.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
127
Top 10%
Top 1%
Average
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