COMPARISON BETWEEN MAXIMUM LIKELIHOOD ESTIMATOR AND ORDINARY LEAST SQUARES BY USING SAZ1 AND SAZ2 AS ALTERNATIVE COMPANION MEAN SQUARES OF ERROR
COMPARISON BETWEEN MAXIMUM LIKELIHOOD ESTIMATOR AND ORDINARY LEAST SQUARES BY USING SAZ1 AND SAZ2 AS ALTERNATIVE COMPANION MEAN SQUARES OF ERROR

Summary/Abstract: Today the robust methods become one of the important subjects that pay attention statisticians because it’s estimators have efficient results that are similar to efficient OLS in case of non existing outliers and become more efficient in case of existing outliers in data. In this research two criteria have been used which are (SAZ1, SAZ2) and will apply on barley data in Iraq between (1960 – 2014). The results that we get and after that we will discuss them in this research and application has been done to compare between Maximum likelihood estimator and Ordinary Least Squares.

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