Evaluation of the predictive performance of the r-k and r-d class estimators |
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Authors: | Issam Dawoud Selahattin Kaçıranlar |
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Institution: | 1. Department of Statistics, Faculty of Sciences and Letters, ?ukurova University, Adana, Turkeyisamdawoud@gmail.com;3. Department of Statistics, Faculty of Sciences and Letters, ?ukurova University, Adana, Turkey |
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Abstract: | Multiple linear regression models are frequently used in predicting unknown values of the response variable y. In this case, a regression model's ability to produce an adequate prediction equation is of prime importance. This paper discusses the predictive performance of the r-k and r-d class estimators compared to ordinary least squares (OLS), principal components, ridge regression and Liu estimators and between each other. The theoretical results are illustrated using Portland cement data and a region is established where the r-k and the r-d class estimators are uniformly superior to the other mentioned estimators. |
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Keywords: | Biased estimation r-k Class estimator r-d Class estimator multicollinearity Prediction Mean Square Error |
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