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Q3 deel 4

R Software Module: rwasp_hierarchicalclustering.wasp (opens new window with default values)
Title produced by software: Hierarchical Clustering
Date of computation: Mon, 05 Nov 2007 03:39:58 -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/05/14zs9l3b2ytx4961194259468.htm/, Retrieved Mon, 05 Nov 2007 11:44:30 +0100
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
70.9 58.4 73 56.8 83.9 69.4 73.2 59.6 76.7 63.6 83.1 68.4 59.8 55.9 68.2 59.1 91.1 66.2 85 66.5 81.6 64.5 78.8 74.5 73 60 74.3 61.4 81.2 70.1 79.9 65.7 79.7 67.1 83.6 70.8 68.6 61.5 666 60.1 83.5 70.1 91.8 73.2 80.5 67.1 84.7 77.4 78.7 66.9 78.4 66 83.1 74 84.8 75.8 80.7 72.2 91.8 78.2 75.3 71.4 71.8 66.3 93 79.9 94.3 81.2 83.7 72.2 95.6 88.4 82.2 72.2 83.4 73 93.1 83.8 88.7 79.7 84.5 79.1 95 84.3 76.6 76.8 73.4 69.3 93 81.3 91 80.9 85.3 76 89.5 90 76.1 72.6 76.1 73.9 91.5 91.2 85.4 83.1 80 80.1 94 91.1 72.6 80.1 80.8 76.3 94.1 93.2 94.9 91.6 91.9 88.5 99.2 103.2 84.7 84.9 93.7 89 106.7 106.9 93.5 91.4 104.8 99.6 103.5 100.6 83.1 88 89.6 89.7 105.7 106.7 110.7 106 110.4 104.4 109 123.7 106 97.1 100.9 95.5 114.3 112.2 101.2 101.4 109.2 106.9 111.6 109.5 91.7 96.4 93.7 93.9 105.7 104.2 109.5 109.2 105.3 108.9 102.8 117.9 100.6 98.2 97.6 101.4 110.3 111.6 107.2 113.6 107.2 110.8 108.1 113.9 97.1 105.5 92.2 95.9 112.2 115.8 111.6 119.9 115.7 107.3 111.3 126.9 104.2 107.8 103.2 105.5 112.7 120.2 106.4 116 102.6 110.4 110.6 120.8 95.2 110.7 89 99.9 112.5 126.8 116.8 128.6 107.2 112.9 113.6 136.6 101.8 113.3 102.6 116.3 122.7 137.5 110.3 126.7 110.5 118.5 121.6 136.4 100.3 120.2 100.7 117.2 123.4 133.3 127.1 134.8 124.1 129.9 131.2 149.5 111.6 118.5 114.2 122.8 130.1 145.7 125.9 133.6 119 130.8 133.8 146.8 107.5 126 113.5 124.4 134.4 145.5 126.8 146.3 135.6 145 139.9 162 129.8 132.2 131 140.2 153.1 164.8 134.1 143.7 144.1 144.2
 
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
10.316227766016833
20.447213595499958
30.538516480713451
40.583095189484536
50.699999999999989
60.707106781186548
70.70710678118655
80.799999999999997
90.806225774829853
100.85440037453175
110.948683298050518
121.01980390271856
131.01980390271856
141.09999999999999
151.14017542509915
161.25630299370947
171.29603046850525
181.29999999999999
191.30000000000001
201.30384048104053
211.43481932115302
221.5
231.55563491861041
241.55563491861041
251.61245154965972
261.62788205960996
271.64012194668567
281.67613137315081
291.69157878903057
301.69705627484772
311.71172427686236
321.72437159370983
331.74642491965731
341.86815416922694
351.93101937404965
361.93132079158281
371.96468827043886
381.97287177262797
392.10651472214494
402.12132034355964
412.24843750706105
422.27806763991128
432.33983212763391
442.40831891575846
452.43310501211928
462.47228630894735
472.48665275119352
482.48976265627660
492.53092855378479
502.59422435421457
512.62598650893371
522.64007575648881
532.69072480941474
542.69429572900313
552.71661554144123
562.74590604354919
572.81780056072107
583.00832179129826
593.0633403748745
603.11126983722082
613.17317326971199
623.21307829568551
633.30849897500198
643.30955692710434
653.35410196624969
663.39104356769034
673.40000000000000
683.47131099154196
693.56499362203059
703.69560312082886
713.94461658466321
724.04470725624791
734.16773319683493
744.16945772330059
754.19183382898345
764.36556079759633
774.48757873539941
784.69564979759638
795.07172597504873
805.07782951095411
815.14636353955988
825.17418849234384
835.29055983586722
845.4470636307191
855.49042652823079
865.81330923427712
875.96336806193126
886.12623548027539
896.66841941167556
906.96447365265285
917.03491293478462
927.8333988501622
938.07485142393862
948.17366276935394
958.21844469569325
968.32166857281224
978.66371788616823
988.69582985961388
998.92016790208863
1008.9969915493635
1019.43322850615253
1029.54598632795085
1039.99018258351224
10410.5186884161067
10511.5199798501706
10611.7018883309000
10712.4925140624205
10813.4937022347464
10913.5130558814380
11013.9025069858074
11114.9992280766656
11217.3437728225694
11317.8256853650811
11418.9485196500554
11520.5949553873986
11620.8967423512191
11721.5196423753871
11822.7407350656507
11922.9424717343899
12023.3344022972283
12124.8446543839002
12226.2213522198346
12330.4101841441181
12446.5839294901808
12555.1368391910238
12655.4723483047786
12764.8656921787995
12888.6717234238108
129114.171150270256
130116.012731980187
131193.822432762099
132267.359651317135
133293.242105471856
134860.785792016768
1351078.82514059193
1362183.46255074505
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/05/14zs9l3b2ytx4961194259468/1bjfz1194259194.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/05/14zs9l3b2ytx4961194259468/1bjfz1194259194.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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