R version 2.6.0 (2007-10-03)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- array(list(99.2,96.7,101.0,99.0,98.1,100.1,100.0,100.0,100.0,111.6,104.9,90.6,122.2,104.9,86.5,117.6,109.5,89.7,121.1,110.8,90.6,136.0,112.3,82.8,154.2,109.3,70.1,153.6,105.3,65.4,158.5,101.7,61.3,140.6,95.4,62.5,136.2,96.4,63.6,168.0,97.6,52.6,154.3,102.4,59.7,149.0,101.6,59.5,165.5,103.8,61.3),dim=c(3,17),dimnames=list(c('Cons','Inc','Price'),1:17))
>  y <- array(NA,dim=c(3,17),dimnames=list(c('Cons','Inc','Price'),1:17))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par7 = '0'
> par6 = '0.5'
> par5 = '0.5'
> par4 = '0.5'
> par3 = '1'
> par2 = 'ward'
> par1 = 'euclidean'
> ylab = 'height'
> xlab = 'cases'
> main = 'Dendrogram'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: Wessa, P., (2007), Agglomerative Nesting (v1.0.1) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_agglomerativehierarchicalclustering.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> par6 <- as.numeric(par6)
> par7 <- as.numeric(par7)
> library(cluster)
> if (par2 == 'flexible')
+ {
+ if (par3 == 1) pm <- c(par4)
+ if (par3 == 3) pm <- c(par4,par5,par6)
+ if (par3 == 4) pm <- c(par4,par5,par6,par7)
+ ag <- agnes(t(y),metric=par1,method=par2,par.method=pm)
+ } else {
+ ag <- agnes(t(y),metric=par1,method=par2)
+ }
> mysub <- paste('Method: ',par2)
> summary(ag)
Object of class `agnes' from call:
 agnes(x = t(y), metric = par1, method = par2) 
Agglomerative coefficient:  0.9520017 
Order of objects:
 [1] 1  2  3  4  5  6  7  8  9  10 11 15 16 14 17 12 13
Merge:
      [,1] [,2]
 [1,]   -1   -2
 [2,]    1   -3
 [3,]   -6   -7
 [4,]  -11  -15
 [5,]  -12  -13
 [6,]   -9  -10
 [7,]   -5    3
 [8,]    4  -16
 [9,]  -14  -17
[10,]   -4    7
[11,]    6    8
[12,]   11    9
[13,]   10   -8
[14,]   12    5
[15,]    2   13
[16,]   15   14
Height:
 [1]   1.676305   3.239856  53.158333  11.665190   8.083522   3.840573
 [7]  24.826397 147.331077   6.200806  14.422321   4.548626   8.638094
[13]  24.782540  10.971782  36.259867   4.644351

136 dissimilarities, summarized :
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
 1.6763 16.8490 32.2880 35.6410 52.2600 84.1240 
Metric :  euclidean 
Number of objects : 17

Available components:
[1] "order"     "height"    "ac"        "merge"     "diss"      "call"     
[7] "method"    "order.lab" "data"     
> postscript(file="/var/www/html/rcomp/tmp/122fl1195140381.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(ag,which.plots=2,main=main,sub=mysub,xlab=xlab,ylab=ylab)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/281pa1195140381.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(ag,which.plots=1,main='Banner',sub=mysub,xlab=ylab,ylab=xlab)
> dev.off()
null device 
          1 
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Agglomerative Nesting (Hierarchical Clustering)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Agglomerative Coefficient',header=TRUE)
> a<-table.element(a,ag$ac)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/3a6ra1195140381.tab") 
> 
> system("convert tmp/122fl1195140381.ps tmp/122fl1195140381.png")
> system("convert tmp/281pa1195140381.ps tmp/281pa1195140381.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.826   0.315   2.851