您的位置:山东大学 -> 科技期刊社 -> 《山东大学学报(理学版)》

《山东大学学报(理学版)》 ›› 2025, Vol. 60 ›› Issue (3): 69-76.doi: 10.6040/j.issn.1671-9352.0.2024.084

• • 上一篇    下一篇

基于线性化技术的变点分位数回归模型的估计与应用

周小英1,2,吉晨1,涂晓艺1*   

  1. 1.海南师范大学数学与统计学院, 海南 海口 571158;2.海南师范大学数据科学与智慧教育教育部重点实验室, 海南 海口 571158
  • 发布日期:2025-03-10
  • 通讯作者: 涂晓艺(2000— ),女,硕士研究生,研究方向为应用统计. E-mail:txy18181281029@163.com
  • 作者简介:周小英(1989— ),女,副教授,博士,研究方向为变点数据建模与应用. E-mail:zhouxy213@163.com*通信作者:涂晓艺(2000— ),女,硕士研究生,研究方向为应用统计. E-mail:txy18181281029@163.com
  • 基金资助:
    国家自然科学地区基金资助项目(72263007);2023年海南省研究生创新科研课题项目(Qhys2023-384)

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

摘要: 构建变点分位数回归模型,该模型由1条直线和1条二次曲线在变点处相交而成,可以灵活处理变点数据,还能捕捉响应变量分布的全貌。由于变点参数的存在,使得模型的损失函数是非凸的,给估计参数带来了挑战。为了解决这个问题,基于线性化技术将损失函数线性化,利用迭代算法,同时得到变点参数和其他参数的估计,给出估计量的区间估计。数值模拟结果表明,本文的估计方法具有良好的相合性和有效性,人均国内生产总值与电力质量数据的实证分析也验证了所提模型和方法的可行性和实用性。

关键词: 变点, 线性-二次分位数回归模型, 线性化技术, 电力质量

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

中图分类号: 

  • O213.9
[1] HUDSON D J. Fitting segmented curves whose join points have to be estimated[J]. Journal of the American Statistical Association, 1966, 61(316):1097-1129.
[2] ROBISON D E. Estimates for the points of intersection of two polynomial regressions[J]. Journal of the American Statistical Association, 1964, 59(305):214-224.
[3] FEDER P I. The log likelihood ratio in segmented regression[J]. The Annals of Statistics, 1975, 3(1):84-97.
[4] CHAPPELL R. Fitting bent lines to data, with applications to allometry[J]. Journal of Theoretical Biology, 1989, 138(2):235-256.
[5] JONES M C, HANDCOCK M S. Determination of anaerobic threshold: what anaerobic threshold?[J]. The Canadian Journal of Statistics, 1991, 19(2):236-239.
[6] HANSEN B E. Inference when a nuisance parameter is not identified under the null hypothesis[J]. Econometrica, 1996, 64(2):413-430.
[7] BAI Jushan. Likelihood ratio tests for multiple structural changes[J]. Journal of Econometrics, 1999, 91(2):299-323.
[8] LERMAN P M. Fitting segmented regression models by grid search[J]. Journal of the Royal Statistical Society Series C: Applied Statistics, 1980, 29(1):77-84.
[9] MUGGEO V M. Estimating regression models with unknown break-points[J]. Statistics in Medicine, 2003, 22(19):3055-3071.
[10] LEE S, SEO M H, SHIN Y. Testing for threshold effects in regression models[J]. Journal of the American Statistical Association, 2011, 106(493):220-231.
[11] 蒋家坤,林华珍,蒋靓,等. 门槛回归模型中门槛值和回归参数的估计[J]. 中国科学(数学),2016,46(4):409-422. JIANG Jiakun, LIN Huazhen, JIANG Liang, et al. Estimation of threshold values and regression parameters in threshold regression model[J]. SCIENTIA SINICA Mathematica, 2016, 46(4):409-422.
[12] PASTOR R, GUALLAR E. Use of two-segmented logistic regression to estimate change-points in epidemiologic studies[J]. American Journal of Epidemiology, 1998, 148(7):631-642.
[13] ZHANG Feipeng, YANG Jiejing, LIU Lei, et al. Generalized linear-quadratic model with a change point due to a covariate threshold[J]. Journal of Statistical Planning and Inference, 2022, 216:194-206.
[14] KOENKER R, BASSETT G. Regression quantiles[J]. Journal of the Econometric Society, 1978, 46(1):33-50.
[15] LI Chenxi, WEI Ying, CHAPPELL R, et al. Bent line quantile regression with application to an allometric study of land mammals speed and mass[J]. Biometrics, 2011, 67(1):242-249.
[16] FERGUSON R, WILKINSON W, HILL R. Electricity use and economic development[J]. Energy Policy, 2000, 28(13):923-934.
[17] WOLDE-RUFAEL Y. Electricity consumption and economic growth: a time series experience for 17 African countries[J]. Energy Policy, 2006, 34(10):1106-1114.
[18] ZHOU Xiaoying, ZHANG Feipeng. A new estimation method for continuous threshold expectile model[J]. Communications in Statistics: Simulation and Computation, 2018, 47(8):2486-2498.
[19] ZHANG Feipeng, ZHENG Shenglin, ZHOU Xiaoying. Bent-cable quantile regression model[J]. Communications in Statistics: Simulation and Computation, 2023, 52(5):2000-2011.
[20] 周小英. 逐段连续线性分位数回归模型的统计推断及其应用[D]. 长沙:湖南大学,2018. ZHOU Xiaoying. Statistical inference and application in continuous threshold linear quantile regression model[D]. Changsha: Hunan University, 2018.
[1] 侯成婷,陈占寿. 基于LSCUSUM方法的RCA(1)模型参数变点检验[J]. 《山东大学学报(理学版)》, 2025, 60(3): 107-115.
[2] 李学文,冯可馨,王小刚. 删失分位数回归模型中的多变点估计[J]. 《山东大学学报(理学版)》, 2025, 60(2): 96-104.
[3] 高琦,戴洪帅,武艳华. 基于MPEWMA控制图的串联排队网络的监测与控制[J]. 《山东大学学报(理学版)》, 2023, 58(8): 104-110, 117.
[4] 朱慧敏,王梓楠,高敏,杨文志. 方差变点模型CUSUM型估计量的相合性[J]. 《山东大学学报(理学版)》, 2023, 58(7): 106-114.
[5] 王小刚,冯可馨. 分段线性删失分位数回归模型的变点估计[J]. 《山东大学学报(理学版)》, 2023, 58(11): 35-44.
[6] 娘毛措, 陈占寿, 成守尧, 汪肖阳. 具有长记忆误差的线性回归模型参数变点的在线监测[J]. 《山东大学学报(理学版)》, 2022, 57(4): 91-99.
[7] 王小刚,李冰. 基于核函数方法的逐段线性Tobit回归模型估计[J]. 《山东大学学报(理学版)》, 2020, 55(6): 1-9.
[8] 梁小林,郭敏,李静. 更新几何过程的参数估计[J]. 山东大学学报(理学版), 2017, 52(8): 53-57.
[9] 王小刚1,2, 王黎明1,3*. 一类面板模型中部分结构变点的检测和估计[J]. J4, 2012, 47(7): 91-99.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] 张京友,张培爱,钟海萍. 进化图论在知识型企业组织结构设计中的应用[J]. J4, 2013, 48(1): 107 -110 .
[2] 张继龙,仪洪勋 . 函数导数分担1个公共值的惟一性[J]. J4, 2006, 41(1): 115 -119 .
[3] 胡明娣1,2,折延宏1,王敏3. L3*系统中逻辑度量空间的拓扑性质[J]. J4, 2010, 45(6): 86 -90 .
[4] 张 慧 . 不完全信息下推广的递归偏好[J]. J4, 2006, 41(1): 62 -68 .
[5] 刘战杰1,马儒宁1,邹国平1,钟宝江2,丁军娣3. 一种新的基于区域生长的彩色图像分割算法[J]. J4, 2010, 45(7): 76 -80 .
[6] . pLaplacian边值问题的多重正解[J]. J4, 2009, 44(7): 79 -82 .
[7] . 中国电力市场的多寡头动态离散模型[J]. J4, 2009, 44(5): 91 -96 .
[8] 汤晓宏1,胡文效2*,魏彦锋2,蒋锡龙2,张晶莹2,. 葡萄酒野生酿酒酵母的筛选及其生物特性的研究[J]. 山东大学学报(理学版), 2014, 49(03): 12 -17 .
[9] 袁瑞强,刘贯群,张贤良,高会旺 . 黄河三角洲浅层地下水中氢氧同位素的特征[J]. J4, 2006, 41(5): 138 -143 .
[10] 郭乔进,丁轶,李宁. 一种基于上下文信息的乳腺肿块ROI检测方法[J]. J4, 2010, 45(7): 70 -75 .