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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: Mon, 10 Nov 2008 06:48:21 -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/t12263249624uzrqbpkpjjpnhr.htm/, Retrieved Mon, 10 Nov 2008 13:49:23 +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/t12263249624uzrqbpkpjjpnhr.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 «
356.2 152823.6 3 12.9 359.5 123780.5 2.9 13.6 368.4 159987.1 2.9 13.7 371 139603.7 2.8 14.1 397.5 177831.2 2.6 15.2 416.7 173656.9 2.5 15.7 413.2 252392 2.8 13 424.3 228029 2.8 13 415 197300 2.8 12.9 421.7 214088 2.7 13.2 422.1 160275 2.7 13.1 429.2 186851 2.7 13.6 452.1 227777 2.5 14.4 471.5 246899 2.4 14.9 488.3 295338 2.3 15.3 506.2 243847 2.3 15.8 517.3 324602 2.2 16.2 538.6 347066 2.3 15.8 545.3 407916 2.6 12.8 546.7 312914 2.7 12.3 540.3 326127 2.7 12.3 549.2 394369 2.6 12.6 563.9 310078 2.5 12.9 581.7 422770 2.5 12.9 590.7 417974 2.4 13.4 594.1 402347 2.5 13.1 604 360809 2.4 13.1 628.1 298289 2.3 13.7 662.4 375873 2.2 14.5 688.6 407210 2.2 15 705.9 413968 2.3 15 701.5 457532 2.4 14.3 686.2 695731 2.5 13.5 645.7 544623 2.5 12.7 668.7 292833 2.4 13.1 696.7 534403 2.4 13.3 715.5 517030 2.3 13.8 741.4 455714 2.2 14 754.3 471401 2.2 14.1 771.3 451493 2 15 797.7 480615 2 15.2 809.9 568272 2.2 14.2 790.1 650780 2.4 12.7 830.3 553643 2.4 13 847.7 780711 2.3 13.2 834.8 650724 2.4 13 824.5 586345 2.5 12.4 764.6 725173 2.5 12.3 780 701257 2.6 11.9 803.2 859063 2.5 12.2 751.1 789842 2.7 11.5 755.2 512707 2.7 11.4 708.2 780845 3.1 10.1 685.4 637804 3 10.4 680 640694 3.4 10.7 710.6 553416 3.3 11.2 702.8 554622 3.5 10.7 656.3 616736 4.1 9.2 575.6 536994 4.7 7.6 567.2 407237 4.4 8 545.2 618796 5.4 6.6
 
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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001


Summary of Dendrogram
LabelHeight
171.6531925318055
2124.582502784300
3193.459298044834
4253.532818388468
5256.634253364589
6292.866010318706
7891.65398990007
81376.65271777009
91525.17850102865
101818.43782956691
112062.99579737817
122511.48840530869
132593.83576773858
142836.05222800991
152890.00508823082
163052.19739040580
174007.65637374264
184174.34418681548
194323.18297207046
204769.81126172688
215526.79626999223
226234.19368602382
237407.54553219458
247730.03783438595
258341.81171118877
269214.10227911542
279645.84589400013
2810449.0096726915
2911035.0223067666
3012021.2559215867
3113743.1558770175
3215823.2041872056
3317209.2025249430
3418073.0059893201
3518335.5117630905
3621526.7121697593
3724666.5342516227
3825351.258154075
3925556.4504791965
4033729.8074901515
4137133.7729956332
4238031.8360255116
4341878.6417124545
4448938.1633974727
4558252.661344417
4661681.799869617
4763088.5291410162
4866197.7512619982
4994376.9183873508
50107328.861374614
51109841.866183081
52161090.048119989
53229807.967157944
54335788.983949456
55376208.566570517
56596416.474463056
57784768.613751835
581178542.99842793
592453703.56788934
606043367.08905466
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t12263249624uzrqbpkpjjpnhr/1ifxg1226324895.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t12263249624uzrqbpkpjjpnhr/1ifxg1226324895.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t12263249624uzrqbpkpjjpnhr/2xnmi1226324895.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t12263249624uzrqbpkpjjpnhr/2xnmi1226324895.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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Software written by Ed van Stee & Patrick Wessa


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