Development Of Nonparametric Geographically Weighted Regression Using Truncated Spline Approach

Abstract

Nonparametric geographically weighted regression with truncated spline approach is a new method of statistical science. It is used to solve the problems of regression analysis of spatial data if the regression curve is unknown. This method is the development of nonparametric regression with truncated spline function approach to the analysis of spatial data. Spline truncated approach can be a solution for solving the modeling problem of spatial data analysis if the data pattern between the response and the predictor variables is unknown or regression curve is not known. This study focused on finding the estimators of the model nonparametric geographically weighted regression by maximum likelihood estimator (MLE) and then these estimators are investigated the unbiased property. The results showed nonparametric geographically weighted regression with truncated spline approach can be used in spatial data to solve problems regression curve that cannot be identified.