Tree-structured model diagnostics for linear regression

Nonparametric Regression Model with Tree-structured Response

Highly developed science and technology from the last two decades motivated the study of complex data objects. In this paper, we consider the topological properties of a population of tree-structured objects. Our interest centers on modeling the relationship between a tree-structured response and other covariates. For tree objects, this poses serious challenges since most regression methods rel...

Tree Structured Interpretable Regression

Stein Type Estimators for Disturbance Variance in Linear Regression Model

This article has no abstract.

A WEIGHTED LINEAR REGRESSION MODEL FOR IMPERCISE RESPONSE

A weighted linear regression model with impercise response and p-real explanatory variables is analyzed. The LR fuzzy random variable is introduced and a metric is suggested for coping with this kind of variables. A least square solution for estimating the parameters of the model is derived. The result are illustrated by the means of some case studies.

Tree Structured Non - Linear Signal

We develop a low complexity non-parametric method of nonlinear prediction based on adaptive partitioning of the phase space associated with an observed process. The partitioning method is implemented with a fast recursive algorithm which successively reenes the partition by dyadic splitting. The algorithm discovers the best partition using a Pearson Chi-square test which is equivalent to maximi...