An ARL-Unbiased Modified np-Chart for Autoregressive Binomial Counts

Author:

Morais Manuel Cabral1ORCID,Wittenberg Philipp2ORCID,Cruz Camila Jeppesen3

Affiliation:

1. Department of Mathematics & CEMAT (Center for Computational and Stochastic Mathematics), Instituto Superior Técnico — Universidade de Lisboa , Av. Rovisco Pais, 1049-001 Lisboa , Portugal

2. Department of Mathematics and Statistics , Helmut Schmidt University , Holstenhofweg 85, 22043 Hamburg , Germany

3. Instituto Superior Técnico , Universidade de Lisboa , Av. Rovisco Pais, 1049-001 Lisboa , Portugal

Abstract

Abstract Independence between successive counts is not a sensible premise while dealing, for instance, with very high sampling rates. After assessing the impact of falsely assuming independent binomial counts in the performance of np-charts, such as the one with 3-σ control limits, we propose a modified np-chart for monitoring first-order autoregressive counts with binomial marginals. This simple chart has an in-control average run length (ARL) larger than any out-of-control ARL, i.e., it is ARL-unbiased. Moreover, the ARL-unbiased modified np-chart triggers a signal at sample t with probability one if the observed value of the control statistic is beyond the lower and upper control limits L and U. In addition to this, the chart emits a signal with probability γ L {\gamma_{L}} (resp. γ U {\gamma_{U}} ) if that observed value coincides with L (resp. U). This randomization allows us to set the control limits in such a way that the in-control ARL takes the desired value ARL 0 {\operatorname{ARL}_{0}} , in contrast to traditional charts with discrete control statistics. Several illustrations of the ARL-unbiased modified np-chart are provided, using the statistical software R and resorting to real and simulated data.

Funder

Fundação para a Ciência e a Tecnologia

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Discrete Mathematics and Combinatorics,Statistics, Probability and Uncertainty,Safety, Risk, Reliability and Quality,Statistics and Probability

Reference25 articles.

1. M. A. Al-Osh and A. A. Alzaid, Binomial autoregressive moving average models, Comm. Statist. Stochastic Models 7 (1991), no. 2, 261–282.

2. M. Anastasopoulou and A. C. Rakitzis, EWMA control charts for monitoring correlated counts with finite range, J. Appl. Stat. 49 (2022), no. 3, 553–573.

3. D. Brook and D. A. Evans, An approach to the probability distribution of cusum run length, Biometrika 59 (1972), 539–549.

4. C. J. Cruz, Cartas com ARL sem viés para processos i.i.d. e AR(1) com marginais binomiais (on ARL-unbiased charts for i.i.d. and binomial AR(1) counts), Master’s thesis, Universidade de Lisboa, 2019.

5. C. J. Geyer and G. D. Meeden, An R package for UMP and UMPU tests, 2004, https://CRAN.R-project.org/package=ump.

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