摘要
在缺失响应变量的不完全数据下,对半参数回归模型进行研究.利用最小二乘和局部线性回归拟合方法建立缺失数据下半参数回归模型参数分量和非参数分量的局部线性估计.在适当的条件下,得到^βn,^nσ的渐近正态性和^gn(t)最优弱收敛速度.
The semiparametric regression model was investigated for the case of response data missing. The local linearity estimations of parametric and nonparametric components in semiparametric regression model were made by using a method of local linear regressive fitting in combination with LS method. In an appropriate condition, the ^βn,^nσ of their asymptotic normalities and the ^gn(t) of optimal weak convergence rate were obtained.
出处
《兰州理工大学学报》
CAS
北大核心
2007年第5期151-155,共5页
Journal of Lanzhou University of Technology
关键词
半参数回归模型
局部线性回归光滑
渐近正态性
缺失数据
最优弱收敛速度
semiparametric regression model
local linear regressive smoothness
asymptotic normality
data missing
optimal weak convergence rate