反映变量有误差时线性回归分析  

Estimation of linear error-in-covariables models with validation data

作　　者：高镔[1] 陈莉莉[2] 

机构地区：[1]黑龙江大学信息科学与技术学院,黑龙江哈尔滨150080 [2]黑龙江大学数学科学学院,黑龙江哈尔滨150080

出　　处：《佳木斯大学学报（自然科学版）》2007年第1期120-121,共2页Journal of Jiamusi University：Natural Science Edition

摘　　要：在许多实际问题中准确测得感兴趣的变量可能是很困难的,或者所需成本很高.因此通常用可观测的替代变量来代替.本文不对真变量和替代变量间关系作任何模型假设,利用主要数据和核实数据,基于最小二乘方法和核方法,应用参数方法获得的估计量,并证明了的渐近正态性.Many variables of intrest are difficult or expensive to be measured accurately and hence are usually replaced by surrogate variables. In this paper, without specifying any structure equafions and distribution assumption of the true variable given the surrogate variable , a parametric method with the primary de ta is employed to obtain the estimator of β based the least-squared criterion and kernel method with the help of validation data. The asymptotic normality of the estiomator of β is derived.

关 键 词：线性模型 核实数据 渐近正态性 

分 类 号：O241.1[理学—计算数学]