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Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS)

ISSN:2141-7016

Article Title: ESTIMATION OF BIVARIATE REGRESSION DATA VIA THEIL'S ALGORITHM
by Ekezie Dan Dan and Opara, Jude

Abstract:
This paper is on the estimation of bivariate regression data using Theil's algorithm. This method was adopted since all errors in the y-direction are not normally distributed (i.e. the do not follow a Gaussian distribution) for the commonly used least squares regression method for fitting an equation into a set of (x,y)-data points using the Kolmogorov Smirnov test. The algorithms for Theils were stated in this paper. The data used for this research were collected from selected primary schools in Owerri Municipal, Imo State Nigeria. The data were on weights and shoulder heights of 100 randomly selected pupils in primary four, five and six. The use of a programming language software known as "R Development" was used to write an appropriate program in this paper. From the analysis, the result revealed that there exists a significant relationship between weights and shoulder heights of primary school pupils, and the estimated fitted theil's is and it was observed that both the intercept and slope are significant.
Keywords: theil's regression, weighted theil's regression, weighted median, OLS, pairwise slope
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ISSN: 2141-7016

Editor in Chief.

Prof. Gui Yun Tian
Professor of Sensor Technologies
School of Electrical, Electronic and Computer Engineering
University of Newcastle
United Kingdom

 

 

Copyright © Journal of Emerging Trends in Engineering and Applied Sciences 2010