Single-step change point estimation in nonlinear profiles using maximum likelihood estimation Online publication date: Wed, 05-Dec-2018
by Ali Ghazizadeh; Hashem Mahlooji; Ahmad Taher Azar; Mahdi Hamid; Mahdi Bastan
International Journal of Intelligent Engineering Informatics (IJIEI), Vol. 6, No. 6, 2018
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.
Online publication date: Wed, 05-Dec-2018
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Engineering Informatics (IJIEI):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org