Ahmad, Maizah Hura and Adnan, Robiah and Lau, Chik Kong and Mohd. Daud, Zalina (2005) Comparing leastsquares and goal programming estimates of linear regression parameter. Matematika, 21 (2). pp. 101112. ISSN 01278274

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Abstract
A regression model is a mathematical equation that describes the relationship between two or more variables. In regression analysis, the basic idea is to use past data to fit a prediction equation that relates a dependent variable to independent variable(s). This prediction equation is then used to estimate future values of the dependent variable. The leastsquares method is the most frequently used procedure for estimating the regression model parameters. However, the method of leastsquares is biased when outliers exist. This paper proposes goal programming as a method to estimate regression model parameters when outliers must be included in the analysis.
Item Type:  Article 

Subjects:  Q Science > QA Mathematics 
Divisions:  Science 
ID Code:  8795 
Deposited By:  Zalinda Shuratman 
Deposited On:  12 May 2009 07:01 
Last Modified:  11 Oct 2017 01:54 
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