Empirical Likelihood Confidence Region for Parameters in Semi-linear Errors-in-Variables Models

Kong, E. (2006) Empirical Likelihood Confidence Region for Parameters in Semi-linear Errors-in-Variables Models. Empirical Likelihood Confidence Region for Parameters in Semi-linear Errors-in-Variables Models, Volume (1). pp. 153-168. (Full text available)

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Abstract

This paper proposes a constrained empirical likelihood confidence region for a parameter in the semi-linear errors-in-variables model. The confidence region is constructed by combining the score function corresponding to the squared orthogonal distance with a constraint on the parameter, and it overcomes that the solution of limiting mean estimation equations is not unique. It is shown that the empirical log likelihood ratio at the true parameter converges to the standard chi-square distribution. Simulations show that the proposed confidence region has coverage probability which is closer to the nominal level, as well as narrower than those of normal approximation of generalized least squares estimator in most cases. A real data example is given.

Item Type: Article
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Efang Kong
Date Deposited: 29 Jun 2011 13:35
Last Modified: 25 Nov 2011 16:38
Resource URI: http://kar.kent.ac.uk/id/eprint/23881 (The current URI for this page, for reference purposes)
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