Some Robust Estimation Methods and Their Applications

Tolga Zaman and Kamil Alakuş

Alphanumeric Journal, 2016, vol. 3, issue 2, 73-82

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.

Keywords: Average Absolute Deviations; Coefficient of Determination; Least Square Errors Methods; Robust Regression Methods (search for similar items in EconPapers)
JEL-codes: C40 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:anm:alpnmr:v:3:y:2016:i:2:p:73-82

DOI: 10.17093/aj.2015.3.2.5000152703

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