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R Software Module: rwasp_hierarchicalclustering.wasp (opens new window with default values)
Title produced by software: Hierarchical Clustering
Date of computation: Sun, 04 Nov 2007 03:18:23 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Nov/04/syxo8fw6ezlu2mp1194171386.htm/, Retrieved Sun, 04 Nov 2007 11:16:26 +0100
 
User-defined keywords:
ws4, q2
 
Dataseries X:
» Textbox « » Textfile « » CSV «
8.1 7.7 8.5 8.2 7.8 8.6 8 7.7 8.5 8.1 7.7 8.5 8.3 7.7 9 8.2 7.7 9 8.1 7.6 8.8 7.7 7.5 8 7.6 7.4 7.9 7.7 7.4 8.1 8.2 7.5 9.3 8.4 7.6 9.4 8.4 7.6 9.4 8.6 8.1 9.3 8.4 7.8 9 8.5 8 9.1 8.7 7.9 9.7 8.7 7.9 9.7 8.6 7.8 9.6 7.4 6.7 8.3 7.3 6.6 8.2 7.4 6.6 8.4 9 7.7 10.6 9.2 7.9 10.9 9.2 8 10.9 8.5 7.7 9.6 8.3 7.5 9.3 8.3 7.6 9.3 8.6 7.8 9.6 8.6 7.8 9.5 8.5 7.7 9.5 8.1 7.4 9 8.1 7.5 8.9 8 7.2 9 8.6 7.5 10.1 8.7 7.6 10.2 8.7 7.6 10.2 8.6 7.8 9.5 8.4 7.7 9.3 8.4 7.7 9.3 8.7 8.2 9.4 8.7 8.2 9.3 8.5 8.1 9.1 8.3 7.8 9 8.3 7.8 8.9 8.3 7.7 9 8.1 6.7 9.8 8.2 6.7 10 8.1 6.7 9.8 8.1 7.2 9.4 7.9 6.9 9 7.7 6.8 8.9 8.1 7.2 9.3 8 7.1 9.1 7.7 6.9 8.8 7.8 6.9 8.9 7.6 6.7 8.7 7.4 6.5 8.6 7.7 6.6 9.1 7.9 6.6 9.3 7.6 6.5 8.9
 
Text written by user:
 
Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!


Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001


Summary of Dendrogram
LabelHeight
10
20
30
40
50
60
70
80
90
100.0999999999999996
110.0999999999999996
120.0999999999999996
130.0999999999999996
140.0999999999999996
150.0999999999999996
160.0999999999999996
170.0999999999999996
180.0999999999999996
190.141421356237309
200.141421356237309
210.141421356237309
220.141421356237309
230.141421356237309
240.141421356237310
250.141421356237310
260.141421356237310
270.141421356237310
280.141421356237310
290.173205080756887
300.173205080756887
310.173205080756887
320.223606797749978
330.223606797749979
340.223606797749980
350.22360679774998
360.244948974278317
370.244948974278317
380.282842712474618
390.282842712474619
400.28284271247462
410.300000000000000
420.346410161513775
430.412310562561766
440.412310562561766
450.469041575982343
460.5
470.509901951359279
480.591607978309962
490.616441400296898
500.648074069840786
510.663324958071079
520.748331477354789
531.03440804327886
541.11803398874990
551.20415945787923
561.31529464379659
571.40356688476182
582.08566536146142
592.44131112314674
603.58608421540822
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/04/syxo8fw6ezlu2mp1194171386/1yj3h1194171497.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/04/syxo8fw6ezlu2mp1194171386/1yj3h1194171497.ps (open in new window)


 
Parameters:
par1 = complete ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
 
R code (references can be found in the software module):
par3 <- as.logical(par3)
par4 <- as.logical(par4)
if (par3 == 'TRUE'){
dum = xlab
xlab = ylab
ylab = dum
}
x <- t(y)
hc <- hclust(dist(x),method=par1)
d <- as.dendrogram(hc)
str(d)
mysub <- paste('Method: ',par1)
bitmap(file='test1.png')
if (par4 == 'TRUE'){
plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub)
} else {
plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub)
}
dev.off()
if (par2 != 'ALL'){
if (par3 == 'TRUE'){
ylab = 'cluster'
} else {
xlab = 'cluster'
}
par2 <- as.numeric(par2)
memb <- cutree(hc, k = par2)
cent <- NULL
for(k in 1:par2){
cent <- rbind(cent, colMeans(x[memb == k, , drop = FALSE]))
}
hc1 <- hclust(dist(cent),method=par1, members = table(memb))
de <- as.dendrogram(hc1)
bitmap(file='test2.png')
if (par4 == 'TRUE'){
plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub)
} else {
plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub)
}
dev.off()
str(de)
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of Dendrogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Label',header=TRUE)
a<-table.element(a,'Height',header=TRUE)
a<-table.row.end(a)
num <- length(x[,1])-1
for (i in 1:num)
{
a<-table.row.start(a)
a<-table.element(a,hc$labels[i])
a<-table.element(a,hc$height[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
if (par2 != 'ALL'){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of Cut Dendrogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Label',header=TRUE)
a<-table.element(a,'Height',header=TRUE)
a<-table.row.end(a)
num <- par2-1
for (i in 1:num)
{
a<-table.row.start(a)
a<-table.element(a,i)
a<-table.element(a,hc1$height[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
 





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Software written by Ed van Stee & Patrick Wessa


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