A Bayesian variable Selection Approach to Nonparametric Regression

Abstract

the importance of study focuses on methods related to smoothing of Nonparametric Regression functions. This is for the purpose of producing the best methods convenient for various models. And for the Distribution Random error, in its Normal cases. Thus, the most important purpose of the research, is to find what the studies so far, have offered in the field of Nonparametric Regression. Also to find alternative or modified methods; which are reliable for the treatment of conditions of failure regarding the methods in use, as well as to alleviate the some methods, especially those related to Bayesian procedures. One of the most outstanding aims of the research focuses on the study of Nonparametric Regression using Bayesian variable selection. This suggests a modified technique to be reliable and of less complexity than the A simulation model has been performed for a number of models .To verify the performance of such methods, many criteria have been carried out.