 Usage:  ckm = kmeans (x, b, it, {w, {m}})  
 
 Input:

  x                      n x p matrix data matrix 
                         
  b                      n x 1 matrix: Initial partition (for example random generated 
                         numbers of clusters 1,2,...,K 
                         
  it                     maximal number of iterations 
                         
  w                      p x 1 matrix with the weights of column points 
                         
  m                      n x 1 matrix of weights (masses) of row points 
                         
 Output:

  cm.g                   n x 1 matrix containing the final partition which gives a 
                         inimum sum of within cluster variances 
                         
  cm.c                   k x p matrix of means (centroids) of the K clusters 
                         
  cm.v                   k x p matrix of within cluster variances divided by the weight 
                         (mass) of clusters 
                         
  cm.s                   k x 1 matrix of the weight (mass) of clusters 
                         
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(C) MD*TECH Method and Data Technologies, 17.8.2000
