An information-theoretic approach to the measurement error model

Amjad D. Al-Nasser

doi:https://doi.org/10.59170/stattrans-2010-001

An information-theoretic approach to the measurement error model

Amjad D. Al-Nasser Statistics in Transition new series, vol. 11, 2010, 1, pages: 9-24 Published online: 1 July 2010 https://doi.org/10.59170/stattrans-2010-001

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ABSTRACT

In this paper, the idea of generalized maximum entropy estimation approach (Golan et al. 1996) is used to fit the general linear measurement error model. A Monte Carlo comparison is made with the classical maximum likelihood estimation (MLE) method. The results showed that, the GME is outperformed the MLE estimators in terms of mean squared error. A real data analysis is also presented.

KEYWORDS

Measurement Error Model, Generalized Maximum Entropy, Maximum Likelihood

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