回归模型参数的变点检测方法研究

Abstract

Abstract:

This paper constructs a method to detect the change point of regression model parameters based on the non-stationary measurement index (NS). Under the premise of selecting the appropriate parameter estimation method and window size, the residual sequence of the sample in the window and the corresponding NS value are calculated by judging the stationarity of the residual sequence within the window to achieve the purpose of change point detection. A series of two-segment regression models are constructed for experimental verification. The results show that this method can effectively detect the position of the change point of the two-segment regression model. The experimental results of comparison with other methods also show that the method is more accurate in the detection of regression model parameter change points.

Key words: Regression model, Change point detection, Non-stationary measure

CLC Number:

O212

Jinhui Zheng,Jinghu Yu,Yiming Ding,Zeyu Bao. Research on Change-Point Detection for Parameters in Regression Model[J].Acta mathematica scientia,Series A, 2021, 41(4): 1124-1134.

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Figures/Tables 11

References 27

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变点位置$l_{1}+1$	无变点	11	41	101	161	191
模型四	100	94.5	98.5	96.5	98.5	99
模型五	100	95	94.5	95.5	99.5	99
模型六	100	94.5	97.5	98	97	98.5

方法	LAD			NS
变点位置	31	81	181	31	81	181
一元线性	79.256	77.196	77.890	1.178	0.702	0.970
多元线性	74.172	76.543	74.306	0.684	0.489	1.015
非线性	133.999	111.789	141.534	23.933	16.690	19.350

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Research on Change-Point Detection for Parameters in Regression Model

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Figures/Tables 11

References 27

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变点位置$l_{1}+1$	无变点	11	41	101	161	191
模型一	100	95.5	96	98	99	99
模型二	100	96.5	97	99	98	99
模型三	100	95.5	97	97.5	97.5	99

变点位置$l_{1}+1$	无变点	11	41	101	161	191
模型七	100	90	93	95.5	96	95.5
模型八	100	96	92	94	96.5	96.5
模型九	100	92.5	94	92	95.5	98