 Usage:  cw = wardcont (x, k, l)  

 

 Input:



  x                      n x p matrix of n row points to be clustered (the 

                         elements must be >= 0, with positive marginal 

                         sums) 

                         

  k                      scalar the maximum number of clusters of rows 

                         

  l                      scalar the maximum number of clusters of columns 

                         

 Output:



  cw.y                   n x l matrix correspondence analysis scores of the 

                         row points (l = min(n-1,p-1) 

                         

  cw.z                   p x l matrix: correspondence analysis scores of the 

                         column points 

                         

  cw.r                   n x 1 matrix: Partition of n points into k clusters 

                         

  cw.c                   p x 1 matrix: Partition of p points into l clusters 

                         

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(C) MD*TECH Method and Data Technologies, 21.9.2000

