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A Markov Chain Approach for Average Run Length of EWMA and CUSUM Control Chart Based on ZINB Model

C. Chananet, P. Areepong, S. Sukparungsee


In this paper, we proposed the Markov Chain Approach (MCA) to evaluate the Average Run Length (ARL) of Exponentially Weighted Moving Average (EWMA) and Cumulative Sum charts (CUSUM) when zero-inflated counted are observed in a negative binomial model. Furthermore, the efficiency of the MCA is compared with Monte Carlo Simulation via the CPU times which the former is much saving computational times used when compared with the latter method.


Exponentially Weighted Moving Average control chart, Cumulative Sum chart, Zero-inflated negative binomial, Average Run Length (ARL), Markov Chain Approach, computational times.

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