联合均值与方差模型的变量选择  

Variable selection in joint mean and variance models

作　　者：吴刘仓[1,2] 张忠占[1] 徐登可[1] 

机构地区：[1]北京工业大学应用数理学院,北京100124 [2]昆明理工大学理学院,昆明650093

出　　处：《系统工程理论与实践》2012年第8期1754-1760,共7页Systems Engineering-Theory & Practice

基　　金：国家自然科学基金(10971007,11126309);北京市教委科技计划(JC006790201001);云南省自然科学基金(2009ZC039M);昆明理工大学博士科研启动基金(2009-024)

摘　　要：在许多应用方面.特别在经济领域和工业产品的质量改进试验中,非常有必要对方差建模.推广经典的正态回归模型,对联合均值与方差模型提出一种同时对均值模型和方差模型的变量选择方法.提出的惩罚极大似然估计具有相合性和oracle性质.随机模拟和实例研究结果表明该模型和方法是有用和有效的.In many applications, particularly in the econometric area and industrial quality improvement experiments, there is a great need to model the variance. A unified procedure was proposed to simultane- ously select significant variables in joint mean and variance models which provide a useful extension of the classical normal regression models. It is further shown that the presented penalized estimator enjoys the consistency and the oracle property. Simulation and practice show that this model and method are useful and effective.

关 键 词：异方差模型 联合均值与方差模型 惩罚极大似然估计 变量选择 

分 类 号：O212.1[理学—概率论与数理统计]