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Journal: IMPACT : International Journal of Research in Applied, Natural and Social Sciences ( IMPACT : IJRANSS ) (Vol.5, No. 5)

Publication Date:

Authors : ;

Page : 69-80

Keywords : Marshall– OlkinExtended Burr III; Maximum Likelihood; M-estimator; Robust estimator; Outliers;

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The parameter estimation of the Marshall– Olkin extended Burr III (MOEBIII) distribution, which is a generalization of the Burr III distribution is considered. The maximum likelihood (ML) estimation of the parameters of the MOEBIIIdistribution is introduced by Al-Saiariet al. (2016). However,ML is often used to estimate the parameters of the Burr III distribution; this method is very sensitive to the presence of outliers in the data. This paper presents M-estimation as a robust method, based on the quantile function to estimate the parameters of the MOEBIII distribution for complete data with outliers. A simulation study and areal data are used to illustratethe performance of M-estimator and ML estimator. The numerical results show that the M-estimator, generally is appropriate than the ML, in terms of the bias and mean square error when there are outliers in the data.

Last modified: 2017-06-17 18:13:23