Some Robust Estimation Methods and Their Applications
Journal Title: Alphanumeric Journal - Year 2015, Vol 3, Issue 2
Abstract
This study examines robust regression methods which are used for the solution of problems caused by the situations in which the assumptions of LSM technique, which is commonly used for the prediction of linear regression models, cannot be used. Robust estimators are not influenced by small deviations and discrepancies. For this purpose, some robust regression techniques which are used in situations in which the assumptions cannot be made were introduced and parameter estimation algorithms of these techniques were analyzed. Regression models of the methods of Lad, Weighted –M regression, Theil regression and Least Median Squares, coefficients of determination and average absolute deviations were calculated and the results were discussed as to which of these methods gave better results.
Authors and Affiliations
Tolga Zaman, Kamil Alakuş
Keywords
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- EP ID EP196265
- DOI 10.17093/aj.2015.3.2.5000152703
- Views 148
- Downloads 0
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