<strong>Paper Title</strong><br>
Mixed Estimator of Kernel and Fourier Series in Nonparametric Regression<br>
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<strong>Abstract</strong><br>
Lets paired the observation   follow the additive nonparametric regression model   where  
  and  Random errors   is a normal distribution with mean 0 and variance  . The aim of this study is obtain a mixed estimator   In order to accomplish the aim, the regression curve  is approached by kernel with bandwidths   and the regression curve component   is fourier series where it is approached by   with oscillation paremeter  M. The estimator   is   where    Based on Penalized Least Squares (PLS) method
 with smoothing parameter  , the estimator   is   and   So that, the mixed estimator   is 
 
where   Matrix   and   are depended on bandwidths parameter  , smoothing parameter   and oscillation paremeter  M. Optimal  ,   and M can be obtained by using Generalized Cross Validation (GCV). 
  
Keywords- Mixed Nonparametric Regression, Kernel, Fourier Series