JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2025, Vol. 60 ›› Issue (3): 69-76.doi: 10.6040/j.issn.1671-9352.0.2024.084

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Estimation and application of the change-point quantile regression model based on linearization technique

ZHOU Xiaoying1,2, JI Chen1, TU Xiaoyi1*   

  1. 1. School of Mathematics and Statistics, Hainan Normal University, Haikou 571158, Hainan, China;
    2. Key Laboratory of Data Science and Smart Education, Ministry of Education, Hainan Normal University, Haikou 571158, Hainan, China
  • Published:2025-03-10

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Abstract: The change-point quantile regression model constructed by the intersection of a straight line and a quadratic curve at a change point. This model can flexibly handle change point data and capture the overall distribution of the response variable. Due to the presence of the change point parameter, the models loss function is non-convex, which is a challenge for parameter estimation. To address this issue, the loss function is linearized based on the linearization technique combining with an iterative algorithm, which can simultaneously estimate the change point and other parameters. The interval estimation theory for the estimators is also derived. Numerical simulation results indicate that the proposed estimation method exhibits good consistency and effectiveness. Empirical analysis of per capita GDP and power quality data further verifies the feasibility and practicality of the proposed model and method.

Key words: change point, linear quadratic quantile regression model, linearization technique, power quality

CLC Number: 

  • O213.9
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