Monitoring distributional changes of squared residuals in GARCH models

Li, Fu-Xiao; Tian, Zheng; Chen, Zhanshou; Qi, Peiyan

doi:10.1080/03610926.2014.995819

Cited by 1 publication

(2 citation statements)

References 23 publications

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“…For the ith component of ( ) Since ≠ δ 0 and δ is a constant, as → ∞ m Putting together (7), (8),(9) and(10), the proof of Theorem 3.4 is complete.…”

mentioning

confidence: 91%

“…In the past few decades, studies of change-point detection have attracted a great deal of attention in fields such as statistics, engineering, economics, climatology and bioscience. For surveys, we refer to the studies by Csörgö and Horváth [1], Perron [2], Gombay [3], Chen and Tian [4], Na et al [5], Zou et al [6], Ross [7], Robbins et al [8], Li et al [9], Cao et al [10] and Chen [11]. Most of these studies deal with the classical linear regression model either with independent identical distribution errors or assuming some type of dependence.…”

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confidence: 99%

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Sequential change-point detection in a multinomial logistic regression model

Chen

Xiao

2020

Open Mathematics

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Change-point detection in categorical time series has recently gained attention as statistical models incorporating change-points are common in practice, especially in the area of biomedicine. In this article, we propose a sequential change-point detection procedure based on the partial likelihood score process for the detection of changes in the coefficients of multinomial logistic regression model. The asymptotic results are presented under both the null of no change and the alternative of changes in coefficients. We carry out a Monte Carlo experiment to evaluate the empirical size of the proposed procedure as well as its average run length. We illustrate the method by using data on a DNA sequence. Monte Carlo experiments and real data analysis demonstrate the effectiveness of the proposed procedure.

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“…For the ith component of ( ) Since ≠ δ 0 and δ is a constant, as → ∞ m Putting together (7), (8),(9) and(10), the proof of Theorem 3.4 is complete.…”

mentioning

confidence: 91%