 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, 17.8.2000
