Evaluation of the predictive performance of the r-k and r-d class estimators

Issam Dawoud and Selahattin Kaçıranlar

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 8, 4031-4050

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.

Date: 2017
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DOI: 10.1080/03610926.2015.1076482

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