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Various EDA topics

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 02:38:22 -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/eovkbeoz0eqfb6q1194169316.htm/, Retrieved Sun, 04 Nov 2007 10:41:58 +0100
 
User-defined keywords:
Q2 Ward Method
 
Dataseries X:
» Textbox « » Textfile « » CSV «
106,7 97,3 93,5 104,8 124,9 110,2 101 94,7 105,6 132 125,9 113,2 112,9 118,3 151,4 100,1 101 99,2 89,9 108,9 106,4 105,7 105,6 90,2 121,3 114,8 113,9 113 107 123,4 81,3 86,4 83,1 64,5 90,3 87 96,5 81,1 92,6 79,3 104,2 103,3 96,9 95,8 117,2 108 114,9 104,3 94,3 116,9 105 105,8 97,7 91,2 120,8 94,5 94,2 102,6 86,3 96,1 92 98,4 89,9 77,6 100,8 95,9 99,4 96 82,5 105,3 108,8 108,8 112,7 97,7 116,1 103,4 112,6 107,1 83,3 112,8 102,1 104,4 106,2 84,2 114,5 110,1 112,2 121 92,8 117,2 83,2 81,1 101,2 77,4 77,1 82,7 97,1 83,2 72,5 80,1 106,8 112,6 105,1 88,8 120,3 113,7 113,8 113,3 93,4 133,4 102,5 107,8 99,1 92,6 109,4 96,6 103,2 100,3 90,7 93,2 92,1 103,3 93,5 81,6 91,2 95,6 101,2 98,8 84,1 99,2 102,3 107,7 106,2 88,1 108,2 98,6 110,4 98,3 85,3 101,5 98,2 101,9 102,1 82,9 106,9 104,5 115,9 117,1 84,8 104,4 84 89,9 101,5 71,2 77,9 73,8 88,6 80,5 68,9 60 103,9 117,2 105,9 94,3 99,5 106 123,9 109,5 97,6 95 97,2 100 97,2 85,6 105,6 102,6 103,6 114,5 91,9 102,5 89 94,1 93,5 75,8 93,3 93,8 98,7 100,9 79,8 97,3 116,7 119,5 121,1 99 127 106,8 112,7 116,5 88,5 111,7 98,5 104,4 109,3 86,7 96,4 118,7 124,7 118,1 97,9 133 90 89,1 108,3 94,3 72,2 91,9 97 105,4 72,9 95,8 113,3 121,6 116,2 91,8 124,1 113,1 118,8 111,2 93,2 127,6 104,1 114 105,8 86,5 110,7 108,7 111,5 122,7 98,9 104,6 96,7 97,2 99,5 77,2 112,7 101 102,5 107,9 79,4 115,3 116,9 113,4 124,6 90,4 139,4 105,8 109,8 115 81,4 119 99 104,9 110,3 85,8 97,4 129,4 126,1 132,7 103,6 154 83 80 99,7 73,6 81,5 88,9 96,8 96,5 75,7 88,8 115,9 117,2 118,7 99,2 127,7 104,2 112,3 112,9 88,7 105,1 113,4 117,3 130,5 94,6 114,9 112,2 111,1 137,9 98,7 106,4 100,8 102,2 115 84,2 104,5 107,3 104,3 116,8 87,7 121,6 126,6 122,9 140,9 103,3 141,4 102,9 107,6 120,7 88,2 99 117,9 121,3 134,2 93,4 126,7 128,8 131,5 147,3 106,3 134,1 87,5 89 112,4 73,1 81,3 93,8 104,4 107,1 78,6 88,6 122,7 128,9 128,4 101,6 132,7 126,2 135,9 137,7 101,4 132,9 124,6 133,3 135 98,5 134,4 116,7 121,3 151 99 103,7 115,2 120,5 137,4 89,5 119,7 111,1 120,4 132,4 83,5 115 129,9 137,9 161,3 97,4 132,9 113,3 126,1 139,8 87,8 108,5 118,5 133,2 146 90,4 113,9 133,5 146,6 154,6 97,1 142,9 102,1 103,4 142,1 79,4 95,2 102,4 117,2 120,5 85 93
 
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'Gwilym Jenkins' @ 72.249.127.135


Summary of Dendrogram
LabelHeight
11.81934053986603
23.4957116585897
33.63180395946697
44.33474336033865
55.22206855565876
65.60267793113257
76
86.04648658313239
96.107372593841
106.45368112010501
116.81102048154313
126.8622153857191
137.01284535691469
147.66016096709536
157.71686464828818
168.29095893126965
178.85607136375944
188.94475193585276
198.95153618101385
209.06587006304414
219.07634287585039
229.39912978430005
239.66436754267965
249.8777521198984
2510.2817793422634
2611.1657039324978
2711.4150218295894
2811.7454217764764
2911.9050409491106
3012.0474063598768
3112.0660681251185
3212.1260051129793
3312.2913149777137
3412.3211200789539
3512.5654287630785
3612.9172238594827
3713.4925905592662
3813.8837443883003
3915.1014826756714
4015.2849599279815
4115.7076414524906
4216.2680147602663
4316.5576265235264
4416.6203200001141
4516.867127793433
4617.4489871995578
4717.6846354763138
4817.6884716426138
4917.7946157752727
5017.9805592724417
5119.9488838810722
5220.0366097422212
5322.8638541990587
5423.0728482355722
5523.1032243727837
5625.0706386629349
5725.6955506647825
5828.00457801722
5929.2728543193178
6030.7275486798671
6131.5113788522284
6232.0615732511673
6332.7013742245969
6437.0368002015006
6537.4196528028941
6641.7856700368903
6744.249656928956
6848.1239203011091
6949.6756216885307
7050.3853980081709
7152.7048133360341
7252.9049742776570
7377.7036951161522
74106.168172009213
75161.084586632303
76183.422136471555
77199.396670718375
78382.339082324229
79850.031712563636
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/04/eovkbeoz0eqfb6q1194169316/12auc1194169097.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/04/eovkbeoz0eqfb6q1194169316/12auc1194169097.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')
}
 





Copyright

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa


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