Applicability of the ACE algorithm for multiple regression in hydrogeology |
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| Authors: | Peter Szucs Roland N Horne |
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| Institution: | (1) Department of Hydrogeology and Engineering Geology, University of Miskolc, 3515 Miskolc-Egyetemvaros, Hungary;(2) Department of Energy Resources Engineering, Stanford University, Stanford, CA 94305-2220, USA |
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| Abstract: | This paper introduces the alternating conditional expectation (ACE) algorithm of Breiman and Friedman (J Am Stat Assoc 80:580–619,
1985) for estimating the transformations of a response and a set of predictor variables in multiple regression problems in hydrogeology.
The proposed nonparametric approach can be applied easily for estimating the optimal transformations of different hydrogeological
data to obtain maximum correlation between observed variables. The approach does not require a priori assumptions of a functional
form, and the optimal transformations are derived solely based on the data set. The advantages and applicability of this new
approach to solve different multiple regression problems in hydrogeology or in Earth Sciences are illustrated by means of
theoretical investigations and case studies. It is demonstrated that the ACE method has certain advantages in some fitting
problems of hydrogeology over the traditional multiple regression. Based on our knowledge, this is the first application of
the ACE algorithm to analyze and interpret groundwater data. |
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| Keywords: | Alternating conditional expectation Nonparametric approach Multiple regression Hydrogeology Most frequent value |
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