Regression trees with moderating effects

This paper proposes a regression tree methodology that considers the relationships among variables belonging to different levels of a data matrix which is characterized by a hierarchical structure. In such way we consider two kinds of partitioning criteria dealing with non parametric regression analysis. The proposal is based on a generalization of Classification and Regression Trees algorithm (CART) that considers a different role played by moderating variables. In the work are showed some applications on real and simulated dataset to compare the proposal with classical approaches.