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The asymptotic normality of an adjusted least squares estimator in a multivariate vector errors-in-variables regression model


Author: I. O. Sen’ko
Translated by: N. Semenov
Original publication: Teoriya Imovirnostei ta Matematichna Statistika, tom 88 (2013).
Journal: Theor. Probability and Math. Statist. 88 (2014), 175-190
MSC (2010): Primary 62J12
DOI: https://doi.org/10.1090/S0094-9000-2014-00929-1
Published electronically: July 24, 2014
MathSciNet review: 3112643
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Abstract | References | Similar Articles | Additional Information

Abstract: An adjusted least squares estimator in a linear multivariate vector error-in-variables regression model is considered in this paper. Conditions for the asymptotic normality of this estimator are given. A modification of the estimator is constructed whose asymptotic properties are the same as those of the adjusted least squares estimator and which is stable even if a sample is small.


References [Enhancements On Off] (What's this?)

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Additional Information

I. O. Sen’ko
Affiliation: Department of Mathematical Analysis, Faculty for Mechanics and Mathematics, National Taras Shevchenko University, Volodymyrs’ka Street, 64, Kyiv 01601, Ukraine
Email: ivan{\textunderscore}senko@ukr.net

DOI: https://doi.org/10.1090/S0094-9000-2014-00929-1
Keywords: Error-in-variables models, adjusted least squares estimator, asymptotic normality, small samples
Received by editor(s): October 25, 2012
Published electronically: July 24, 2014
Article copyright: © Copyright 2014 American Mathematical Society

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