JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2025, Vol. 60 ›› Issue (2): 96-104.doi: 10.6040/j.issn.1671-9352.0.2024.021

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Estimation of multiple change points for censored quantile regression model

LI Xuewen1, FENG Kexin2, WANG Xiaogang2*   

  1. 1. School of Business, North Minzu University, Yinchuan 750021, Ningxia, China;
    2. School of Mathematics and Information Science, North Minzu University, Yinchuan 750021, Ningxia, China
  • Published:2025-02-14

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Abstract: To simultaneously estimate the number of change points, the location of change points and the model parameters in censored quantile regression model, a linearization technique is employed to obtain estimators for above parameters. This approach overcomes the issues of non-differentiability and non-convexity objective function at the change points. It is capable of capturing the relationship between response and covariate of interest that changes across multiple change points. Furthermore, the proposed estimators strike a balance between flexibility and interpretability, making them become a useful tool for identifying and explaining change points. Simulation studies show that the estimators demonstrate robustness in both homoscedastic and heteroscedastic conditions across various quantile levels. An empirical analysis reveals the existence of two change points and their change point effects.

Key words: estimation multiple change point, censored data, quantile regression model, linearization technique

CLC Number: 

  • O212.2
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