Combined regression models |
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| Authors: | Enrique Castillo Carmen Castillo Ali S. Hadi José M. Sarabia |
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| Affiliation: | (1) Department of Applied Mathematics and Computational Sciences, University of Cantabria, 39005 Santander, Spain;(2) Department of Civil Engineering, University of Castilla-La Mancha, Ciudad Real, Spain;(3) Department of Mathematics, The American University in Cairo, Cairo, Egypt;(4) Department of Statistical Science, Cornell University, Ithaca, NY, USA;(5) Department of Economics, University of Cantabria, Santander, Spain |
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| Abstract: | The goal of this paper is two-fold. First, new regression models obtained by combinations of the least squares (LS), minimax (MM), and the least sum of absolute deviations (LSAD) are proposed. Second, measures for assessing the influence of observations on the fitted models are suggested. The paper is interdisciplinary because the theory behind the proposed method draws from results in the operations research area. The methods are illustrated by their application to some examples and graphical illustrations are given. |
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| Keywords: | Duality Dual variables Least absolute value Least squares Local influence Mathematical programming Minimax Optimization problems |
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