Title: Single-step change point estimation in nonlinear profiles using maximum likelihood estimation
Authors: Ali Ghazizadeh; Hashem Mahlooji; Ahmad Taher Azar; Mahdi Hamid; Mahdi Bastan
Addresses: Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran ' Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran ' Faculty of Computers and Information, Benha University, Benha, Egypt; School of Engineering and Applied Sciences, Nile University, Giza, Egypt ' School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran ' Department of Industrial Engineering, University of Eyvanekey, Garmsar, Iran
Abstract: In this work, we study the change point problem in nonlinear profiles. A maximum likelihood estimator (MLE) is proposed for single step change point detection in nonlinear profiles. Due to the complexity of estimating the parameters of the nonlinear model by MLE, this estimator is based on the difference between the response variables and in-control profile curve with no need of estimating the regression parameters. Since the likelihood function (or its logarithm) is complicated enough to deter one from estimating the time of change by an exact method we resort to techniques in numerical analysis for this purpose. Finally, the performance of the proposed estimator is tested through simulation studies.
Keywords: statistical process control; nonlinear profile; step change point; maximum likelihood estimator.
International Journal of Intelligent Engineering Informatics, 2018 Vol.6 No.6, pp.527 - 547
Published online: 28 Nov 2018 *Full-text access for editors Access for subscribers Purchase this article Comment on this article