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. 