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Modern Stochastics: Theory and Applications


Estimation in a linear errors-in-variables model under a mixture of classical and Berkson errors
Volume 8, Issue 3 (2021), pp. 373–386
Pub. online: 26 July 2021      Type: Research Article      Open accessOpen Access
Received
10 March 2021
Revised
16 June 2021
Accepted
28 June 2021
Published
26 July 2021

Abstract

A linear structural regression model is studied, where the covariate is observed with a mixture of the classical and Berkson measurement errors. Both variances of the classical and Berkson errors are assumed known. Without normality assumptions, consistent estimators of model parameters are constructed and conditions for their asymptotic normality are given. The estimators are divided into two asymptotically independent groups.

References

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Copyright
© 2021 The Author(s). Published by VTeX
Open access article under the CC BY license.

Keywords
Linear errors-in-variables model mixture of the classical and Berkson errors consistent estimators asymptotically independent estimators

MSC2010
62505 62H12

Funding
Research is supported by the National Research Fund of Ukraine grant 2020.02/0026.

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