摘要
在随机缺失(MAR)机制下利用经验似然方法构造了线性回归模型中误差方差的估计.并在一定条件下,证明了该估计的渐近正态性,由此得出当误差的分布不对称时,该估计的渐近方差比常用估计的渐近方差小.
Under the mechanism of random absence(MAR),the empirical likelihood method is used to construct the estimate of error variance in the linear regression model.under certain conditions,the asymptotic normality of the estimate is proved,and the asymptotic variance of the estimate is smaller than that of the commonly used estimate when the error distribution is asymmetric.
作者
陈晓英
秦永松
CHEN Xiao-ying;QIN Yong-song(School of Mathematics and Computer Science,Hezhou University,Hezhou 542899,China;School of Mathematics and Statistics,Guangxi Normal University,Guilin 541006,China)
出处
《数学的实践与认识》
北大核心
2020年第4期240-248,共9页
Mathematics in Practice and Theory
基金
国家自然科学基金(11671102)
广西自然科学基金(2017GXNSFAA198349).
关键词
随机缺失
线性回归模型
经验似然
渐近正态性
lack of machine
linear regression model
empirical likelihood
asymptotically normal
