Code:

     library("xclust")   
     randomize(0)
     x  = normal(200, 5)        ; generate random data with 3 clusters
     x1 = x - #(2,1,3,0,0)'
     x2 = x + #(1,1,3,1,0.5)'
     x3 = x + #(0,0,1,5,1)'
     x  = x1|x2|x3
     w  = 1./var(x)                 ; compute column variances
     m  = matrix(rows(x))           ; generate true partition
     t  = matrix(200)|matrix(200).+1|matrix(200).+2
     ca = adaptive (x, 3, w, m, t)  ; apply adaptive clustering; 

© MD*Tech - Method and Data Technologies, generated on 19.7.2000 .