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

Ismat M. Ibrahim ()
Additional contact information
Ismat M. Ibrahim: Polytechnic University of Duhok, Duhok, Iraq

Yearbook of the Faculty of Economics and Business Administration, Sofia University, 2018, vol. 15, issue 1, 41-58

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.

Keywords: Outliers; Robust estimates; Outliers Detection; Leverage Points. (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.feba.uni-sofia.bg/sko/yrbook/Yearbook15-03.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sko:yrbook:v:15:y:2018:i:1:p:41-58

Access Statistics for this article

More articles in Yearbook of the Faculty of Economics and Business Administration, Sofia University from Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria Contact information at EDIRC.
Bibliographic data for series maintained by Prof. Teodor Sedlarski ().