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  • Fundamentals of Contemporary Mathematical Sciences
  • Volume:5 Issue:1
  • Generalized Kibria-Lukman Prediction Approximation in Linear Mixed Models

Generalized Kibria-Lukman Prediction Approximation in Linear Mixed Models

Authors : Özge Kuran
Pages : 25-35
Doi:10.54974/fcmathsci.1263030
View : 34 | Download : 33
Publication Date : 2024-01-31
Article Type : Research Paper
Abstract :One of the new suggested prediction method is the Kibria-Lukman\'s prediction approach under multicollinearity in linear mixed models and in this article, the generalized Kibria-Lukman estimator and predictor are introduced to combat multicollinearity problem. The comparisons between the proposed generalized Kibria-Lukman estimator/predictor and several other estimators/predictors, namely the best linear unbiased estimator/predictor and Kibria-Lukman estimator/predictor are done by using the matrix mean square error criterion. Lastly, the selection of the biasing parameter is given and to demonstrate the performance of our new de ned prediction method, the greenhouse gases data analysis is made.
Keywords : Linear mixed model, mean square error, generalized Kibria Lukman predictor, multicollinearity

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