 Usage:  {mh, clo, cup} = regci(x {,h {,alpha {,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, 20% of the 

                         range of x[,1] is used. 

                         

  alpha                  confidence level, If not given, 0.05 is used. 

                         

  K                      string, kernel function on [-1,1]. 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. 

                         

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

                         second column contains the lower confidence 

                         bounds for that grid. 

                         

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

                         second column contains the upper confidence 

                         bounds for that grid. 

                         

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

