The m-delay Autoregressive Model with Application

作     者：Manlika Ratchagit BenchawanWiwatanapataphee Nikolai Dokuchaev 

作者机构：School of Electrical EngineeringComputing and Mathematical SciencesCurtin UniversityPerthAustralia. 

出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)

年 卷 期：2020年第122卷第2期

页      面：487-504页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：The authors would like to thank the associate editor and the anonymous referees for their valuable comments and suggestions 

主　　题：Delay autoregressive model least squares method brute-force technique. 

摘      要：The classical autoregressive(AR)model has been widely applied to predict future data usingmpast observations over five *** the classical AR model required m unknown parameters,this paper implements the AR model by reducing m parameters to two parameters to obtain a new model with an optimal delay called as the m-delay AR *** derive the m-delay AR formula for approximating two unknown parameters based on the least squares method and develop an algorithm to determine optimal delay based on a brute-force *** performance of them-delay AR model was tested by comparing with the classical AR *** results,obtained from Monte Carlo simulation using the monthly mean minimum temperature in PerthWestern Australia from the Bureau of Meteorology,are no significant difference compared to those obtained from the classical AR *** confirms that the m-delay AR model is an effective model for time series analysis.