New weighted geometric mean method to estimate the slope of measurement error model
Article
Article Title | New weighted geometric mean method to estimate the slope of measurement error model |
---|---|
ERA Journal ID | 32342 |
Article Category | Article |
Authors | Saqr, Anwar (Author) and Khan, Shahjahan (Author) |
Editors | Scott, Melvin |
Journal Title | Journal of Applied Statistical Science |
Journal Citation | 22 (3-4), pp. 261- 280 |
Number of Pages | 18 |
Year | 2014 |
Place of Publication | United States |
ISSN | 1067-5817 |
Web Address (URL) | https://www.novapublishers.com/catalog/product_info.php?products_id=61597 |
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. |
Keywords | linear regression models; measurement error models; re ection of points; ratio of error variances; geometric mean estimator; OLS-bisector |
ANZSRC Field of Research 2020 | 490501. Applied statistics |
490599. Statistics not elsewhere classified | |
490509. Statistical theory | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Buraimi University College, Bahrain |
School of Agricultural, Computational and Environmental Sciences | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q3w93/new-weighted-geometric-mean-method-to-estimate-the-slope-of-measurement-error-model
Download files
844
total views322
total downloads0
views this month0
downloads this month