 Usage:  mh = lpregest (x, h {,p {,K} {,d}})  

 

 Input:



  x                      n x 2, the data. In the first column the 

                         independent, in the second column the 

                         dependent variable. 

                         

  h                      scalar, bandwidth. If not given, the rule of thumb 

                         bandwidth computed by lpregrot is used. 

                         

  p                      integer, order of polynomial. If not given, 

                         p=1 (local linear) is used. p=0 yields the 

                         Nadaraya-Watson estimator. 

                         

  K                      string, kernel function on [-1,1] or Gaussian 

                         kernel "gau". If not given, the Quartic kernel 

                         "qua" is used. 

                         

  d                      scalar, discretization binwidth. d must be smaller 

                         than h. If not given, the minimum of h/3 and 

                         (max(x[,1])-min(x[,1]))/100 is used. 

                         

 Output:



  mh                     m x 2 matrix, the first column is a grid and the 

                         second column contains the regression estimate on 

                         that grid. 

                         

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(C) MD*TECH Method and Data Technologies, 21.9.2000

