摘要
基于不确定理论,提出了一类新的不确定分位数回归模型.在不确定理论的框架下,给出了分位点、损失函数等相关概念的定义以及相关定理的证明,并利用优化方法,给出了不确定分位数回归模型的参数估计、预测值及预测区间.最后,通过数值模拟及案例分析验证了不确定分位数回归模型的鲁棒性和有效性.
In this paper,a new uncertain quantile regression model based on uncertainty theory is proposed.Under the framework of uncertainty theory,the definitions of uncertain quantile and uncertain loss function are given and the related theorems are proved.Then,parameter estimates,forecast values and confidence intervals are obtained for the uncertain quantile regression model by using the optimization method of mathematical programming.Finally,two numerical simulations are shown to illustrate the efectiveness and robustness of the model.
作者
李天用
胡锡健
LI Tianyong;HU Xijian(School of Mathematics and System Sciences,Xinjiang University,Urumqi Xinjiang 830017,China)
出处
《新疆大学学报（自然科学版）（中英文）》
CAS
2022年第5期530-541,共12页
Journal of Xinjiang University(Natural Science Edition in Chinese and English)
基金
The research is supported by National Natural Science Foundation of People’s Republic of China(11961065)。
关键词
不确定理论
分位数回归
参数估计
最优化
uncertainty theory
quantile regression
parameter estimate
optimization
