New weighted geometric mean method to estimate the slope of measurement error model

Saqr, Anwar and Khan, Shahjahan (2014) New weighted geometric mean method to estimate the slope of measurement error model. Journal of Applied Statistical Science, 22 (3-4). 261- 280. ISSN 1067-5817

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Abstract

This paper introduces a new weighted geometric mean (WG) estimator to fit regression line when both the response and explanatory variables are subject to measurement errors. The proposed estimator is based on the mathematical relationship between the vertical and orthogonal distances of the observed points and the regression line (cf. Saqr and Khan, 2012). It minimizes the orthogonal distance of the observed points from the unfitted line. The WG estimator is less sensitive to the ratio of error variances. It is a better alternative than the currently used geometric mean (GM) and OLS-bisector estimators. Extensive simulation results show that the proposed WG estimator is much more stable than the geometric mean and OLS-bisector estimators. The mean absolute error of the WG estimator is consistently smaller than the geometric mean and OLS-bisector estimators.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences
Date Deposited: 23 Nov 2017 00:31
Last Modified: 23 Nov 2017 00:31
Uncontrolled Keywords: linear regression models; measurement error models; re ection of points; ratio of error variances; geometric mean estimator; OLS-bisector
Fields of Research : 01 Mathematical Sciences > 0104 Statistics > 010401 Applied Statistics
01 Mathematical Sciences > 0104 Statistics > 010499 Statistics not elsewhere classified
01 Mathematical Sciences > 0104 Statistics > 010405 Statistical Theory
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970101 Expanding Knowledge in the Mathematical Sciences
URI: http://eprints.usq.edu.au/id/eprint/30461

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