Change point detection in INAR(p) models via likelihood ratio scanning method

被引：0

作者：

Chen, Jiaqi ^{[1
]}

Lu, Feilong ^{[1
]}

机构：

[1] Univ Sci & Technol Liaoning, Coll Sci, Anshan, Peoples R China

来源：

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION | 2025年 / 95卷 / 02期

关键词：

Change point detection; likelihood ratio; Poisson distribution; INAR models; SERIES;

D O I：

10.1080/00949655.2024.2425790

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, we consider an integer-valued autoregressive (INAR) model. Based on the likelihood ratio scanning method (LRSM), the numbers and locations of the piecewise stationary INAR process change points are discussed. The minimum description length (MDL) function of the INAR model is given. Moreover, we also study the case when the sum of coefficients in each segment of the model tends to 1 and make adjustments to the MDL criterion in the LRSM. In this way, the accuracy of change point detection is improved. In the end, simulation experiments and real data analysis are conducted to illustrate the efficiency of the LRSM.

引用

页码：351 / 366

页数：16

共 29 条

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