Nonparametric Regression Estimation under Kernel Polynomial Model for Unstructured Data

Abstract

The nonparametric estimation(NE) of kernel polynomial regression (KPR) model is a powerful tool to visually depict the effect of covariates on response variable, when there exist unstructured and heterogeneous data. In this paper we introduce KPR model that is the mixture of nonparametric regression models with bootstrap algorithm, which is considered in a heterogeneous and unstructured framework. Also, the optimal properties of estimators have been considered. Finallly, we have studied a real heterogeneous and unstructured data using the KPR model.