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Cluster -25 en +25 groep 7

R Software Module: rwasp_hierarchicalclustering.wasp (opens new window with default values)
Title produced by software: Hierarchical Clustering
Date of computation: Thu, 01 Nov 2007 02:44:16 -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/01/i664u0h8otbyvm21193910293.htm/, Retrieved Thu, 01 Nov 2007 10:44:55 +0100
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
140 373 132 371 117 354 114 357 113 363 110 364 107 363 103 358 98 357 98 357 137 380 148 378 147 376 139 380 130 379 128 384 127 392 123 394 118 392 114 396 108 392 111 396 151 419 159 421 158 420 148 418 138 410 137 418 136 426 133 428 126 430 120 424 114 423 116 427 153 441 162 449 161 452 149 462 139 455 135 461 130 461 127 463 122 462 117 456 112 455 113 456 149 472 157 472 157 471 147 465 137 459 132 465 125 468 123 467 117 463 114 460 111 462 112 461 144 476 150 476 149 471 134 453 123 443 116 442 117 444 111 438 105 427 102 424 95 416 93 406 124 431 130 434
 
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
10
21
31
41.41421356237310
51.41421356237310
61.41421356237310
72
82.23606797749979
92.23606797749979
102.23606797749979
112.23606797749979
122.82842712474619
133
143.16227766016838
153.16227766016838
163.16227766016838
173.42300831451815
183.60555127546399
193.60555127546399
203.60555127546399
214.24264068711928
224.24264068711928
234.47213595499958
244.47213595499958
255.05409255338946
265.09901951359278
275.36968341626806
285.3851648071345
295.3851648071345
305.59460848827082
315.81475009280696
325.89779636853229
336.79869268479038
347.14073503395199
357.4980161288279
368.0238642356092
378.03340850144742
388.06225774829855
398.09939788642314
408.24621125123532
419.1200541274224
4210.1980390271856
4310.5586098189921
4411.3792197525585
4512.2633987911162
4613.0690070292362
4716.0412841716290
4816.1702905593681
4916.8412261588121
5017.7173083825026
5117.7942896378464
5217.941562044205
5319.8235995678678
5421.6344504442762
5525.0874723880819
5625.5085754521729
5728.5058937428263
5835.3826179076600
5935.5868328347652
6043.470780118183
6147.1452730394948
6256.5385182089246
6381.5957721635439
6482.7135034244422
6596.1127996962216
66124.703376621690
67189.099566549510
68234.250609789229
69245.504244523435
70505.537626205761
711402.53639154265
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/01/i664u0h8otbyvm21193910293/17js31193910254.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/01/i664u0h8otbyvm21193910293/17js31193910254.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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Software written by Ed van Stee & Patrick Wessa


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