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*The author of this computation has been verified*
R Software Module: rwasp_hierarchicalclustering.wasp (opens new window with default values)
Title produced by software: Hierarchical Clustering
Date of computation: Wed, 12 Nov 2008 06:43:55 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Nov/12/t1226497510atnt0s4t18133ka.htm/, Retrieved Wed, 12 Nov 2008 13:45:14 +0000
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2008/Nov/12/t1226497510atnt0s4t18133ka.htm/},
    year = {2008},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2008},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
 
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Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
98.6 98.1 98.6 98 101.1 98 106.8 111.1 106.8 96.6 93.3 96.7 100.1 100 100.2 107.7 108 107.7 91.5 70.4 92 97.8 75.4 98.4 107.4 105.5 107.4 117.5 112.3 117.7 105.6 102.5 105.7 97.4 93.5 97.5 99.5 86.7 99.9 98 95.2 98.2 104.3 103.8 104.5 100.6 97 100.8 101.1 95.5 101.5 103.9 101 103.9 96.9 67.5 99.6 95.5 64 98.4 108.4 106.7 112.7 117 100.6 118.4 103.8 101.2 108.1 100.8 93.1 105.4 110.6 84.2 114.6 104 85.8 106.9 112.6 91.8 115.9 107.3 92.4 109.8 98.9 80.3 101.8 109.8 79.7 114.2 104.9 62.5 110.8 102.2 57.1 108.4 123.9 100.8 127.5 124.9 100.7 128.6 112.7 86.2 116.6 121.9 83.2 127.4 100.6 71.7 105 104.3 77.5 108.3 120.4 89.8 125 107.5 80.3 111.6 102.9 78.7 106.5 125.6 93.8 130.3 107.5 57.6 115 108.8 60.6 116.1 128.4 91 134 121.1 85.3 126.5 119.5 77.4 125.8 128.7 77.3 136.4 108.7 68.3 114.9 105.5 69.9 110.9 119.8 81.7 125.5 111.3 75.1 116.8 110.6 69.9 116.8 120.1 84 125.5 97.5 54.3 104.2 107.7 60 115.1 127.3 89.9 132.8 117.2 77 123.3 119.8 85.3 124.8 116.2 77.6 122 111 69.2 117.4 112.4 75.5 117.9 130.6 85.7 137.4 109.1 72.2 114.6 118.8 79.9 124.7 123.9 85.3 129.6 101.6 52.2 109.4 112.8 61.2 120.9 128 82.4 134.9 129.6 85.4 136.3 125.8 78.2 133.2 119.5 70.2 127.2 115.7 70.2 122.7 113.6 69.3 120.5 129.7 77.5 137.8 112 66.1 119.1 116.8 69 124.3 127 79.2 134.4 112.1 56.2 121.1 114.2 63.3 122.2 121.1 77.8 127.7 131.6 92 137.4 125 78.1 132.2 120.4 65.1 129.2 117.7 71.1 124.9 117.5 70.9 124.8 120.6 72 128.2 127.5 81.9 134.4 112.3 70.6 118.6 124.5 72.5 132.6 115.2 65.1 123.2 105.4 61.1 112.3
 
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 computational 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
10.299999999999997
20.866025403784439
31.00498756211210
41.14891252930761
51.28452325786651
61.48996644257513
71.50665191733193
81.51657508881031
91.60312195418814
101.60623784042091
111.72916164657906
121.73205080756888
131.74642491965729
141.96468827043884
152.11187120819429
162.19544984001001
172.20513651231144
182.20907220343745
192.28254244210266
202.28910462845192
212.33452350598574
222.51594912508182
232.53574446662119
242.57681974534502
252.64386081328046
262.77058532449966
272.90172362570939
282.99845561883698
293.12564300278747
303.26734797768568
313.37231389578452
323.52278299076171
333.52278299076171
343.62439339021964
353.91241935925077
363.93192065026751
373.95600808897050
384.5459418594782
394.64186944335954
404.7050431050899
414.87266882949687
425.03686410378521
435.16477859074342
445.70119980019328
456.06465168002251
466.24775822887093
476.48052293251887
486.50573778370815
497.21025528344463
507.55040704099927
517.57284653113911
527.58880812543228
537.87781695649246
547.89908376646548
557.92842985716592
568.21712600436276
578.37317627893287
588.38742520331551
599.3880430504072
609.42349702457905
619.42385975563958
6210.0702528040335
6310.1305655820971
6410.5240112075564
6511.4964472540226
6611.7315813085875
6711.7874385126027
6811.8746715537649
6912.0487598520219
7012.0632616362875
7114.5614772412080
7217.0553423117035
7319.1334017828411
7420.9285825777002
7522.5323850220856
7623.3171390729907
7727.0034736049979
7827.2739939916207
7928.479988420788
8034.9335466432876
8137.9812439338702
8244.7313126545005
8367.345151823671
8468.1355071029826
8574.1336254311414
8690.1118076844012
87106.430822697709
88127.127133164643
89191.601770157151
90477.498755121726
91581.923599755596
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t1226497510atnt0s4t18133ka/18kn51226497433.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t1226497510atnt0s4t18133ka/18kn51226497433.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t1226497510atnt0s4t18133ka/2lmdx1226497433.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t1226497510atnt0s4t18133ka/2lmdx1226497433.ps (open in new window)


 
Parameters (Session):
par1 = ward ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
 
Parameters (R input):
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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