Predictive Performance Evaluation of the Kibria-Lukman Estimator

745ba493-1adc-484c-8774-0aa9a3f7a54f20220920053706608wseas:wseasmdt@crossref.orgMDT DepositWSEAS TRANSACTIONS ON MATHEMATICS2224-28801109-276910.37394/23206http://wseas.org/wseas/cms.action?id=40511520221520222110.37394/23206.2022.21https://wseas.com/journals/mathematics/2022.phpPredictive Performance Evaluation of the Kibria-Lukman EstimatorIssamDawoudDepartment of Mathematics, Al-Aqsa University, Gaza, PALESTINEMohamed R.AbonazelDepartment of Applied Statistics and Econometrics, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, EGYPTElsayed TagEldinElectrical Engineering Department, Faculty of Engineering & Technology, Future University in Egypt, New Cairo, EGYPTRegression models are commonly used in prediction, but their predictive performances may be affected by the problem called the multicollinearity. To reduce the effect of the multicollinearity, different biased estimators have been proposed as alternatives to the ordinary least squares estimator. 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