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Comparison Between Maximum Likelihood Estimator And Ordinary Least Squares By Using Saz1 And Saz2 As Alternative Companion Mean Squares Of Error

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  • Ismat M. Ibrahim

    (Polytechnic University of Duhok, Duhok, Iraq)

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.

Suggested Citation

  • Ismat M. Ibrahim, 2018. "Comparison Between Maximum Likelihood Estimator And Ordinary Least Squares By Using Saz1 And Saz2 As Alternative Companion Mean Squares Of Error," Yearbook of the Faculty of Economics and Business Administration, Sofia University, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria, vol. 16(1), pages 145-159, December.
    • Handle: RePEc:sko:yrbook:v:16:y:2018:i:1:p:145-159
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    References listed on IDEAS

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    1. Robert Blattberg & Thomas Sargent, 2010. "Regression With Non-Gaussian Stable Disturbances: Some Sampling Results," World Scientific Book Chapters, in: Greg M Allenby (ed.), Perspectives On Promotion And Database Marketing The Collected Works of Robert C Blattberg, chapter 1, pages 7-16, World Scientific Publishing Co. Pte. Ltd..
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