Change Point Estimation of the Stationary State in Auto Regressive Moving Average Models, Using Maximum Likelihood Estimation and Singular Value Decomposition-based Filtering
- سال انتشار: 1398
- محل انتشار: ماهنامه بین المللی مهندسی، دوره: 32، شماره: 5
- کد COI اختصاصی: JR_IJE-32-5_015
- زبان مقاله: انگلیسی
- تعداد مشاهده: 336
نویسندگان
Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran
Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran
Department of Industrial Engineering, College of Engineering, West Tehran Branch, Islamic Azad University, Tehran, Iran
چکیده
In this paper, for the first time, the subject of change point estimation has been utilized in the stationary state of auto regressive moving average (ARMA) (1, 1). In the monitoring phase, in case the features of the question pursue a time series, i.e., ARMA(1,1), on the basis of the maximum likelihood technique, an approach will be developed for the estimation of the stationary state’s change point. To estimate unidentified parameters following the change point, the dynamic linear model’s filtering was utilized on the basis of the singular decomposition of values. The proposed model has wide applications in several fields such as finance, stock exchange marks and rapid production. The results of simulation showed the suggested estimator’s effectiveness. In addition, a real example on stock exchange market is offered to delineate the application.کلیدواژه ها
Auto Regressive Moving Average Model Change Point Estimation, Dynamic Linear Model, maximum likelihood estimation, Singular Value Decompositionاطلاعات بیشتر در مورد COI
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