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paper

R Software Module: rwasp_hierarchicalclustering.wasp (opens new window with default values)
Title produced by software: Hierarchical Clustering
Date of computation: Sat, 10 Nov 2007 04:28:08 -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/10/t1194693854t248aee242sibph.htm/, Retrieved Sat, 10 Nov 2007 12:24:16 +0100
 
User-defined keywords:
28
 
Dataseries X:
» Textbox « » Textfile « » CSV «
103,1 98,6 98,1 98,6 100,6 98 101,1 98 103,1 106,8 111,1 106,8 95,5 96,6 93,3 96,7 90,5 100,1 100 100,2 90,9 107,7 108 107,7 88,8 91,5 70,4 92 90,7 97,8 75,4 98,4 94,3 107,4 105,5 107,4 104,6 117,5 112,3 117,7 111,1 105,6 102,5 105,7 110,8 97,4 93,5 97,5 107,2 99,5 86,7 99,9 99 98 95,2 98,2 99 104,3 103,8 104,5 91 100,6 97 100,8 96,2 101,1 95,5 101,5 96,9 103,9 101 103,9 96,2 96,9 67,5 99,6 100,1 95,5 64 98,4 99 108,4 106,7 112,7 115,4 117 100,6 118,4 106,9 103,8 101,2 108,1 107,1 100,8 93,1 105,4 99,3 110,6 84,2 114,6 99,2 104 85,8 106,9 108,3 112,6 91,8 115,9 105,6 107,3 92,4 109,8 99,5 98,9 80,3 101,8 107,4 109,8 79,7 114,2 93,1 104,9 62,5 110,8 88,1 102,2 57,1 108,4 110,7 123,9 100,8 127,5 113,1 124,9 100,7 128,6 99,6 112,7 86,2 116,6 93,6 121,9 83,2 127,4 98,6 100,6 71,7 105 99,6 104,3 77,5 108,3 114,3 120,4 89,8 125 107,8 107,5 80,3 111,6 101,2 102,9 78,7 106,5 112,5 125,6 93,8 130,3 100,5 107,5 57,6 115 93,9 108,8 60,6 116,1 116,2 128,4 91 134 112 121,1 85,3 126,5 106,4 119,5 77,4 125,8 95,7 128,7 77,3 136,4 96 108,7 68,3 114,9 95,8 105,5 69,9 110,9 103 119,8 81,7 125,5 102,2 111,3 75,1 116,8 98,4 110,6 69,9 116,8 111,4 120,1 84 125,5 86,6 97,5 54,3 104,2 91,3 107,7 60 115,1 107,9 127,3 89,9 132,8 101,8 117,2 77 123,3 104,4 119,8 85,3 124,8 93,4 116,2 77,6 122 100,1 111 69,2 117,4 98,5 112,4 75,5 117,9 112,9 130,6 85,7 137,4 101,4 109,1 72,2 114,6 107,1 118,8 79,9 124,7 110,8 123,9 85,3 129,6 90,3 101,6 52,2 109,4 95,5 112,8 61,2 120,9 111,4 128 82,4 134,9 113 129,6 85,4 136,3 107,5 125,8 78,2 133,2 95,9 119,5 70,2 127,2 106,3 115,7 70,2 122,7 105,2 113,6 69,3 120,5 117,2 129,7 77,5 137,8 106,9 112 66,1 119,1 108,2 116,8 69 124,3 110 126,3 75,3 134,3 96,1 112,9 58,2 121,7 100,6 115,9 59,7 125
 
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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Summary of Dendrogram
LabelHeight
11.51986841535706
21.97484176581314
32.01246117974981
42.82488937836510
52.90516780926679
62.9698484809835
73.03315017762062
83.05450486986026
93.14006369362151
103.16385840391127
113.53553390593274
123.54541958024717
133.57351367704112
143.9255572852781
153.99624824053762
164.01497197997696
174.03360880601975
184.20119030752
194.24146201208969
204.47995535692043
215.32259335286849
225.37028863283903
235.49636243346452
245.55517776493245
255.56116431211975
265.57584026246159
276.07376492736444
286.56201188660917
296.70987042010081
307.12297742613039
317.56891971418106
327.95201949437366
337.99631006768038
348.02184517427256
358.12065295182214
368.1872419873922
378.21561582749469
388.32886546895794
398.57554662980734
409.0321674102571
419.07524104363074
429.42333855105635
439.48135684894045
449.64624279188536
4510.4527508341106
4610.9016093571052
4711.5697643437436
4811.7393922532449
4911.8997043162546
5012.3623326350073
5112.3878973195615
5213.4201785324492
5314.2240552376252
5414.5176298178522
5514.8035519417472
5616.9181929480329
5717.7726438480242
5817.8845879366242
5917.9796423013800
6019.1654105920298
6120.8181545887518
6223.0932035390893
6324.4867985725525
6424.9013041131454
6525.9603182125375
6631.5420308494674
6736.5159944913662
6837.3895657235242
6947.7613293810131
7047.7771377975562
7154.7250029057309
7257.7723710737579
7370.1473886356615
7471.9044527827645
7571.9538798655109
76138.808091055222
77152.031189639636
78403.878745038168
79507.816613145297
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/10/t1194693854t248aee242sibph/15mtb1194694085.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/10/t1194693854t248aee242sibph/15mtb1194694085.ps (open in new window)


 
Parameters:
par1 = ward ; 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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