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Ward

*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: Mon, 10 Nov 2008 15:13:06 -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/10/t1226355279nvefoikxyxcgczz.htm/, Retrieved Mon, 10 Nov 2008 22:14:39 +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/10/t1226355279nvefoikxyxcgczz.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)
 
Feedback Forum:

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Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
116.1 117.1 118.9 100.3 102.5 107.0 108.8 97.6 102.0 107.0 115.6 89.1 101.3 111.0 95.0 99.1 100.6 108.2 92.8 94.9 100.9 96.3 108.9 96.5 104.2 100.9 109.8 92.6 108.3 107.7 106.1 80.8 108.9 106.2 102.8 89.5 109.9 118.7 98.4 101.4 106.8 116.1 85.7 95.9 112.7 118.1 114.6 92.3 113.4 118.4 129.4 91.2 101.3 110.8 117.7 88.3 97.8 106.4 126.6 80.7 95.0 112.2 103.8 89.9 93.8 108.3 101.5 87.2 94.5 96.0 118.7 86.9 101.4 100.6 119.6 82.8 105.8 107.8 114.8 72.6 106.6 108.4 109.9 81.3 109.7 120.9 106.3 91.2 108.8 117.3 95.0 87.3 113.4 119.7 124.5 83.4 113.7 119.6 140.4 81.7 103.6 111.8 128.8 80.2 98.2 108.1 137.5 74.1 95.5 111.8 113.3 80.6 94.4 105.5 110.3 79.0 95.9 93.6 129.1 79.3 103.2 103.9 128.4 71.2 104.1 100.3 120.3 78.1 127.6 106.6 113.6 68.2 130.3 118.4 96.9 81.0 133.0 106.6 124.7 106.9 140.4 109.8 126.4 123.7 123.5 115.9 131.9 73.7 116.9 111.7 122.5 69.2 115.9 119.8 113.1 72.5 113.1 116.1 99.8 75.7 112.1 103.2 116.0 73.5 112.4 99.0 115.0 70.4 118.9 112.3 114.0 65.7 117.4 104.2 111.0 68.1 115.6 114.0 91.7 62.4 120.7 121.7 90.6 64.7 114.9 107.2 103.3 77.7 122.0 112.8 106.7 85.9 119.6 117.8 111.2 61.0 114.6 113.3 102.9 57.4 118.4 116.1 126.5 75.1 110.9 111.8 115.1 75.9 111.6 110.2 110.2 71.8 114.6 110.0 110.1 72.3 112.1 102.9 103.3 67.3 117.4 110.1 107.7 71.5 114.8 102.7 103.9 67.6 123.4 118.7 114.0 74.2 118.1 109.0 117.2 77.6 121.9 115.7 117.0 76.4 123.3 118.1 116.5 74.2
 
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'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Summary of Dendrogram
LabelHeight
12.57293606605372
22.78926513619628
33.04959013639538
44.25088226136647
54.4698993277254
64.86775327677004
75.32353266168247
85.40647759636531
95.4735728733616
105.55067563455116
115.7159245672951
126.93325320466519
137.24292758489272
147.27942305406137
157.56108457828637
167.78909494100566
178.2395388220458
189.30268778364619
199.32416216075203
209.5812316536028
219.93478736561583
2210.0171141489568
2310.3591767966024
2410.3624321469431
2510.8571804347509
2611.5697882435246
2712.4150574746360
2812.879829191414
2913.1772531280233
3014.4371929400574
3114.6169664103140
3214.842506526864
3314.8596296399774
3414.8800636015085
3515.0614519225805
3615.8150102722386
3715.8767541026108
3817.2862569222107
3918.6021757532703
4018.7117610074520
4118.8211773030117
4219.6522587762426
4319.6996810664725
4421.0644331488876
4523.5230664559955
4624.5074017537682
4725.5054557866368
4832.6812032778592
4932.8222936704997
5033.2005696220011
5134.1171034295239
5245.8841099503659
5355.8717550857903
5460.1145801076398
5568.4854796553501
5682.0120989166368
5787.1936733323854
58120.462352740996
59192.891353888930
60234.539300309508
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t1226355279nvefoikxyxcgczz/1yjmf1226355182.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t1226355279nvefoikxyxcgczz/1yjmf1226355182.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t1226355279nvefoikxyxcgczz/2hl3g1226355182.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t1226355279nvefoikxyxcgczz/2hl3g1226355182.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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