异方差模型两阶段估计的一种新方法  

A new method of two-stage estimation about heteroscedastic model

作　　者：崔蕾[1] 张晓琴[1] 

机构地区：[1]山西大学数学科学学院,山西太原030006

出　　处：《陕西科技大学学报（自然科学版）》2016年第5期179-183,共5页Journal of Shaanxi University of Science & Technology

基　　金：山西省自然科学基金项目(2015011044);山西省国际合作与交流项目(2015081020);山西省高等学校教学改革项目(J2014006)

摘　　要：异方差是线性回归模型中经常出现的问题,解决异方差问题的一个常用的方法是两阶段最小二乘法.当样本容量较小时,通过分组产生重复数据,将会损失大量样本信息,使得两阶段最小二乘法得到的估计结果不具有精确性和有效性.利用正交表将样本容量扩大,并通过分组产生重复数据,进而对数据进行两阶段估计.结果表明,该方法大大降低了估计的误差,得到了更准确的拟合模型.Heteroscedasticity is a problem that often appears in the linear regression model,two-stage least squares method is a common method to solve this problem.When the sample size is small,grouping the samples to produce repeated data will lose a lot of information,and this will lead to the loss of accuracy and effectiveness for the estimation of two-stage least squares method.In this paper,we will expand further samples using orthogonal array,and grouping them to obtain repeated data,finally we can get the estimate by two-stage estimation.Results show that this method will reduce the error of estimation,and get a more accurate fitting model.

关 键 词：异方差 两阶段最小二乘法 分组 正交表 

分 类 号：O212.1[理学—概率论与数理统计]