 Usage:  cd = divisive (x, k, w, m, sv)  
 
 Input:

  x                      n x p matrix of n row points to be clustered 
                         
  k                      scalar number of clusters 
                         
  w                      p x 1 matrix of weights of column points 
                         
  m                      n x 1 matrix of weights (masses) of row points 
                         
  sv                     scalar seed value for random numbers 
                         
                         
 Output:

  cd.p                   n x 1 matrix partition of n points of x into k 
                         clusters 
                         
  cd.n                   k x 1 matrix of number of observations of clusters 
                         
  cd. a                  p x 1 matrix of final (pooled) adaptive weights of 
                         the variables 
                         
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(C) MD*TECH Method and Data Technologies, 17.8.2000
