Alternating conditional expectations: Difference between revisions

Revision as of 20:02, 27 March 2019

Revision as of 08:33, 9 May 2019

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==Introduction==

In statistics, nonlinear transformation of variables is commonly used in practice in regression problems. Alternating conditional expectations (ACE) is one of thesethe methodmethods to find those transformations that produce the best fitting additive model. Knowledge of such transformations aids in the interpretation and understanding of the relationship between the response and predictors.

ACE transform the response variable <math>Y</math> and its predictor variables, <math>X_i</math> to minimize the fraction of variance not explained. The transformation is nonlinear and is obtained from data in an iterative way.