Az ACE algoritmus alkalmazása karsztvízszint adatok hidrogeológia vizsgálatára

Abstract

This paper introduces the alternating conditional expectation (ACE) algorithm 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.