Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0167-9473(01)00033-0
Title: Zero-inflated poisson model in statistical process control
Authors: Xie M., He B. 
Keywords: Average run length
Count data
Hypothesis testing
Power of test
Simulation
Statistical process control
Zero-inflated poisson distribution
Issue Date: 28-Dec-2001
Citation: Xie M., He B. (2001-12-28). Zero-inflated poisson model in statistical process control. Computational Statistics and Data Analysis 38 (2) : 191-201. ScholarBank@NUS Repository. https://doi.org/10.1016/S0167-9473(01)00033-0
Abstract: Poisson distribution has often been used for count related data. However, this model does not provide a good fit to actual data when there is a frequent or excessive number of zero counts. For example, in a near zero-defect manufacturing environment, there are many zero-defect counts even for fairly large sample size. In such a situation, the zero-inflated Poisson distribution is more appropriate. In this paper, the use of this distribution is investigated. In particular, various tests of Poisson distribution and zero-inflated Poisson alternative are compared. When the model is used in statistical process control, control limits can then be derived based on the zero-inflated Poisson model when the Poisson distribution is rejected in favour of the zero-inflated Poisson alternative. Furthermore, sensitivity analysis of such a control chart is also presented. © 2001 Published by Elsevier Science B.V.
Source Title: Computational Statistics and Data Analysis
URI: http://scholarbank.nus.edu.sg/handle/10635/63395
ISSN: 01679473
DOI: 10.1016/S0167-9473(01)00033-0
Appears in Collections:Staff Publications

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