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Blok 8 q2 hierarchical clustering

*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: Thu, 13 Nov 2008 11:06:40 -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/13/t1226599692gtqjkjayggmv5gk.htm/, Retrieved Thu, 13 Nov 2008 18:08:15 +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/13/t1226599692gtqjkjayggmv5gk.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 «
81.1 92.3 95.5 79.3 96.9 95.5 98.7 117.2 104.3 92.5 115.9 116.9 97.7 89.6 110.4 120.8 102.6 84.3 109.5 96.1 89.9 76.3 92.3 100.8 96 80.7 102.1 105.3 112.7 96.3 112.8 116.1 107.1 81 110.2 112.8 106.2 82.9 98.9 114.5 121 90.3 119 117.2 101.2 74.8 104.3 77.1 83.2 70.1 98.8 80.1 105.1 86.7 109.4 120.3 113.3 86.4 170.3 133.4 99.1 89.9 118 109.4 100.3 88.1 116.9 93.2 93.5 78.8 111.7 91.2 98.8 81.1 116.8 99.2 106.2 85.4 116.1 108.2 98.3 82.6 114.8 101.5 102.1 80.3 110.8 106.9 117.1 81.2 122.8 104.4 101.5 68 104.7 77.9 80.5 67.4 86 60 105.9 91.3 127.2 99.5 109.5 94.9 126.1 95 97.2 82.8 114.6 105.6 114.5 88.6 127.8 102.5 93.5 73.1 105.2 93.3 100.9 76.7 113.1 97.3 121.1 93.2 161 127 116.5 84.9 126.9 111.7 109.3 83.8 117.7 96.4 118.1 93.5 144.9 133 108.3 91.9 119.4 72.2 105.4 69.6 107.1 95.8 116.2 87 142.8 124.1 111.2 90.2 126.2 127.6 105.8 82.7 126.9 110.7 122.7 91.4 179.2 104.6 99.5 74.6 105.3 112.7 107.9 76.1 114.8 115.3 124.6 87.1 125.4 139.4 115 78.4 113.2 119 110.3 81.3 134.4 97.4 132.7 99.3 150 154 99.7 71 100.9 81.5 96.5 73.2 101.8 88.8 118.7 95.6 137.7 127.7 112.9 84 138.7 105.1 130.5 90.8 135.4 114.9 137.9 93.6 153.8 106.4 115 80.9 119.5 104.5 116.8 84.4 123.3 121.6 140.9 97.3 166.4 141.4 120.7 83.5 137.5 99 134.2 88.8 142.2 126.7 147.3 100.7 167 134.1 112.4 69.4 112.3 81.3 107.1 74.6 120.6 88.6 128.4 96.6 154.9 132.7 137.7 96.6 153.4 132.9 135 93.1 156.2 134.4 151 91.8 175.8 103.7 137.4 85.7 131.7 119.7 132.4 79.1 130.1 115 161.3 91.3 161.1 132.9 139.8 84.2 128.2 108.5 146 85.8 140.3 113.9 166.5 94.6 174.9 142 143.3 77.1 111.8 97.7 121 76.5 136.6 92.2
 
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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132


Summary of Dendrogram
LabelHeight
13.43365694267788
23.92428337406971
35.44334456010272
46.29603049547887
56.38905313798532
66.4643276916905
76.88331315574121
87.07807601999635
97.21526160301898
108.02620707432844
118.52056336165632
128.66314030822541
139.20326029187484
149.50263121456367
159.5827970864461
169.64782797933012
179.65453261426985
189.71905345185425
199.80510071340422
2010.1557865278865
2110.3038827633082
2210.4488765363889
2310.5057127316522
2410.6985980389956
2511.6651205867286
2611.7961713539548
2712.3309058630512
2812.8359134687778
2913.3157801123329
3013.7124045820179
3114.2433681473618
3214.329442128041
3314.4734468895443
3414.7722768289781
3515.0738541527919
3615.3143723345098
3715.7853633822361
3815.8324965218668
3915.9553431340328
4017.0400070818705
4117.6402947821174
4217.7676672638813
4321.175076601454
4422.0116310525778
4522.3608808547375
4622.5561521541242
4724.5392516742178
4824.7426288670359
4925.809688103501
5028.5722657955422
5129.3010750020238
5229.3188961397423
5329.637081652184
5430.2350138060015
5530.5107647041646
5631.5788413617875
5737.1592855235147
5841.1026523861353
5942.6072937177633
6043.6016258266556
6144.5971306721788
6247.1644635738112
6352.8070735794771
6470.6672846101821
6573.8131078854509
6687.7772186638722
6788.2456640827598
6891.3729454667284
69150.640997487375
70222.730657120609
71372.614554672102
72825.031411230738
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/13/t1226599692gtqjkjayggmv5gk/1kbdl1226599597.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/13/t1226599692gtqjkjayggmv5gk/1kbdl1226599597.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/13/t1226599692gtqjkjayggmv5gk/2smtv1226599597.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/13/t1226599692gtqjkjayggmv5gk/2smtv1226599597.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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