International Journal of Mathematics and Computational Science
Articles Information
International Journal of Mathematics and Computational Science, Vol.4, No.3, Sep. 2018, Pub. Date: Aug. 20, 2018
Estimating Bounded Population Total Using Linear Regression in the Presence of Supporting Information
Pages: 112-117 Views: 324 Downloads: 93
Authors
[01] Lamin Kabareh, Department of Mathematics and Statistics, Pan African University Institute for Basic Sciences, Technology and Innovation (PAUSTI), Juja, Kenya.
[02] Thomas Mageto, Department of Mathematics and Statistical Sciences, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya.
Abstract
Estimation of finite population total using linear regression in the presence of auxiliary information is considered. Model based on linear regression model is proposed. Like the existing estimators, this estimation technique deals with QR decomposition approach based on normalized yearly population totals in order to best fit in a model within a given period of time in this study. The proposed linear regression model technique has shown to be efficient. The empirical study indicated that the linear regression model is efficient and can estimate properly when the QR decomposition approach is applied even in the presence of outliers.
Keywords
Linear, Model, Estimation, Population Total, Supporting Information, QR Decomposition, Regression, Outliers
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