Asymptotically independent estimators in a structural linear model with measurement errors

We consider a structural linear regression model with measurement errors. A new parameterization is proposed, in which the expectation of the response variable plays the role of a new parameter instead of the intercept. This enables us to form three groups of asymptotically independent estimators in...

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Bibliographic Details
Date:2016
Main Authors: Kukush, A. G., Tsaregorodtsev, Ya. V., Shklyar, S. V., Кукуш, О. Г., Царегородцев, Я. В., Шкляр, С. В.
Format: Article
Language:Ukrainian
Published: Institute of Mathematics, NAS of Ukraine 2016
Online Access:https://umj.imath.kiev.ua/index.php/umj/article/view/1937
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Journal Title:Ukrains’kyi Matematychnyi Zhurnal
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Ukrains’kyi Matematychnyi Zhurnal
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Summary:We consider a structural linear regression model with measurement errors. A new parameterization is proposed, in which the expectation of the response variable plays the role of a new parameter instead of the intercept. This enables us to form three groups of asymptotically independent estimators in the case where the ratio of variances of the errors is known and two groups of this kind if the variance of the measurement error in the covariate is known. In this case, it is not assumed that the errors and the latent variable are normally distributed.