 Usage:  {fh, clo, cup} = dencb(x {,h {,alpha {,K} {,d}}})  
 
 Input:

  x                      n x 1 vector, the data. 
                         
  h                      scalar, bandwidth. If not given, the rule of 
                         thumb bandwidth computed by denrot is used 
                         (Silverman's rule of thumb). 
                         
  alpha                  confidence level, If not given, 0.05 is used. 
                         
  K                      string, kernel function on [-1,1] with 
                         K(-1)=K(1)=0. 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)-min(x))/100 is used. 
                         
 Output:

  fh                     m x 2 matrix, the first column is a grid and the 
                         second column contains the density 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, 17.8.2000
