A wavelet approach for profile monitoring of Poisson distribution with application

Profile monitoring is defined as the act of utilizing regression and quality control techniques to monitor the functional relationship between a response variable and one or more regressors. Most of the previous studies focused either on parametric modeling of profiles or assumed the response variable followed a normal distribution, but that is an unrealistic scenario in most cases. In this study, a Haar wavelet approach is applied for profile monitoring of Poisson data. We showed via simulation that, Haar wavelet can outperform parametric models when there is a sudden jump in the profile and concluded with a case study.

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Published in: Communications in Statistics - Simulation and Computation
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
See article on publisher's website: https://dx.doi.org/10.1080/03610918.2018.1563151