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General least product relative error estimation for multiplicative regression models with or without multiplicative distortion measurement errors
Communications in Statistics - Simulation and Computation ( IF 0.9 ) Pub Date : 2020-07-31 , DOI: 10.1080/03610918.2020.1801731
Huili Zhou 1 , Jun Zhang 1
Affiliation  

Abstract

We consider the parameter estimation for multiplicative linear regression models with or without multiplicative distortion measurement errors. For the latter, both the response variable and the covariates are are unobserved and distorted by unknown functions of a commonly observable confounding variable. With or without distortion measurement errors, we propose the general least product relative error estimator, and we discuss the estimation efficiency with the least squares estimators by taking logarithmic transformation. Asymptotic properties for the estimators are established. Simulation studies are conducted to demonstrate the performance of the proposed estimation procedures.



中文翻译:

具有或不具有乘法失真测量误差的乘法回归模型的一般最小乘积相对误差估计

摘要

我们考虑了具有或不具有乘法失真测量误差的乘法线性回归模型的参数估计。对于后者,响应变量和协变量都未被观察到,并且被通常可观察到的混杂变量的未知函数扭曲。无论有无失真测量误差,我们提出了一般最小乘积相对误差估计器,并通过对数变换讨论了最小二乘估计器的估计效率。建立了估计量的渐近性质。进行模拟研究以证明所提出的估计程序的性能。

更新日期:2020-07-31
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