1994Journal of Applied StatisticsRequires access

Poisson and negative binomial dynamics for counted data under CUSUM-type charts

Giovanni Radaelli

Open publisher page 13 citations

Abstract

Control charts for counted data are commonly designed assuming that counts follow Poisson dynamics. However, in various real situations, the true underlying dynamics of the events are more properly modelled by a negative binomial process. This paper examines the consequences of the Poisson approximation to negative binomial dynamics for counts under CUSUM-type schemes. It is essentially found that, on setting up Poisson dyamics for an underlying negative binomial data structure, the real in-control average run length decreases, whereas the sensitivity of the chart is affected less. These results warn against the routine use of the Poisson assumption in planning control charts for counts.

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What this paper is about

Control charts for counted data are commonly designed assuming that counts follow Poisson dynamics. However, in various real situations, the true underlying dynamics of the events are more properly modelled by a negative binomial process. This paper examines the consequences of the Poisson approximation to negative binomial dynamics for counts under CUSUM-type schemes. It is essentially found that, on setting up Poisson dyamics for an underlying negative binomial data structure, the real in-control average run length decreases, whereas the sensitivity of the chart is affected less. These results warn against the routine use of the Poisson assumption in planning control charts for counts.

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Available abstract

Control charts for counted data are commonly designed assuming that counts follow Poisson dynamics. However, in various real situations, the true underlying dynamics of the events are more properly modelled by a negative binomial process. This paper examines the consequences of the Poisson approximation to negative binomial dynamics for counts under CUSUM-type schemes. It is essentially found that, on setting up Poisson dyamics for an underlying negative binomial data structure, the real in-control average run length decreases, whereas the sensitivity of the chart is affected less. These results warn against the routine use of the Poisson assumption in planning control charts for counts.

Key concepts: CUSUM, Negative binomial distribution, Poisson distribution, Count data, Control chart, Statistics, Poisson regression, Mathematics

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