Abstract
The process personnel always seek the opportunity to improve the processes. One of the essential steps for the process improvement is to recognize the starting time or the change point of a process disturbance quickly. Different from the traditional normally distributed assumption for a process, this study considers a process that follows a gamma distribution. The proposed approach combines the commonly used control chart with the Bayesian estimation technique to estimate the change point. Two Bayes estimators corresponding to an informative and a noninformative prior along with maximum likelihood estimation (MLE) are considered. Their efficiency is compared through a series of simulations. The results show that the Bayes estimator with the informative prior is more accurate and more precise when the means of the process before and after the change point time are not too closed. Additionally, the efficiency of the Bayes estimator with the informative prior increases as either the sample size increases or the change point goes away from the origin.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Communications in Statistics - Simulation and Computation
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
