 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, 21.9.2000

