Comparing least-squares and goal programming estimates of linear regression parameter.
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...
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| Format: | Article |
| Language: | en |
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Department of Mathematics, Faculty of Science
2005
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| Online Access: | http://eprints.utm.my/8795/1/MaizahHuraAhmad2005_ComparingLeast-SquaresandGoalProgramming.pdf http://eprints.utm.my/8795/ |
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| _version_ | 1845472080345169920 |
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| author | Ahmad, Maizah Hura Adnan, Robiah Lau, Chik Kong Mohd. Daud, Zalina |
| author_facet | Ahmad, Maizah Hura Adnan, Robiah Lau, Chik Kong Mohd. Daud, Zalina |
| author_sort | Ahmad, Maizah Hura |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | 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 least-squares method is the most frequently used procedure for estimating the regression model parameters. However, the method of least-squares 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. |
| format | Article |
| id | my.utm.eprints-8795 |
| institution | Universiti Teknologi Malaysia |
| language | en |
| publishDate | 2005 |
| publisher | Department of Mathematics, Faculty of Science |
| record_format | eprints |
| spelling | my.utm.eprints-87952017-10-11T01:54:47Z http://eprints.utm.my/8795/ Comparing least-squares and goal programming estimates of linear regression parameter. Ahmad, Maizah Hura Adnan, Robiah Lau, Chik Kong Mohd. Daud, Zalina QA Mathematics 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 least-squares method is the most frequently used procedure for estimating the regression model parameters. However, the method of least-squares 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. Department of Mathematics, Faculty of Science 2005-12 Article PeerReviewed application/pdf en http://eprints.utm.my/8795/1/MaizahHuraAhmad2005_ComparingLeast-SquaresandGoalProgramming.pdf Ahmad, Maizah Hura and Adnan, Robiah and Lau, Chik Kong and Mohd. Daud, Zalina (2005) Comparing least-squares and goal programming estimates of linear regression parameter. Matematika, 21 (2). pp. 101-112. ISSN 0127-8274 |
| spellingShingle | QA Mathematics Ahmad, Maizah Hura Adnan, Robiah Lau, Chik Kong Mohd. Daud, Zalina Comparing least-squares and goal programming estimates of linear regression parameter. |
| title | Comparing least-squares and goal programming estimates of linear regression parameter. |
| title_full | Comparing least-squares and goal programming estimates of linear regression parameter. |
| title_fullStr | Comparing least-squares and goal programming estimates of linear regression parameter. |
| title_full_unstemmed | Comparing least-squares and goal programming estimates of linear regression parameter. |
| title_short | Comparing least-squares and goal programming estimates of linear regression parameter. |
| title_sort | comparing least-squares and goal programming estimates of linear regression parameter. |
| topic | QA Mathematics |
| url | http://eprints.utm.my/8795/1/MaizahHuraAhmad2005_ComparingLeast-SquaresandGoalProgramming.pdf http://eprints.utm.my/8795/ |
| url_provider | http://eprints.utm.my/ |