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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 10:36:33 -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/t1226338684tg6ca8cagl6455y.htm/, Retrieved Mon, 10 Nov 2008 17:38:04 +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/t1226338684tg6ca8cagl6455y.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 «
0.771 493.000 58.972 54.281 0.751 481.000 59.249 63.654 0.766 462.000 63.955 68.918 0.754 457.000 53.785 58.686 0.773 442.000 52.760 67.074 0.781 439.000 44.795 60.183 0.793 488.000 37.348 54.326 0.791 521.000 32.370 54.085 0.878 501.000 32.717 53.564 0.873 485.000 40.974 60.873 0.897 464.000 33.591 53.398 0.885 460.000 21.124 45.164 0.796 467.000 58.608 59.672 0.776 460.000 46.865 56.298 0.788 448.000 51.378 62.361 0.786 443.000 46.235 56.930 0.801 436.000 47.206 62.954 0.811 431.000 45.382 62.431 0.801 484.000 41.227 52.528 0.781 510.000 33.795 54.060 0.778 513.000 31.295 53.093 0.759 503.000 42.625 52.695 0.764 471.000 33.625 52.333 0.754 471.000 21.538 41.747 0.749 476.000 56.421 58.576 0.729 475.000 53.152 57.851 0.740 470.000 53.536 63.721 0.781 461.000 52.408 63.384 0.768 455.000 41.454 61.141 0.754 456.000 38.271 59.231 0.754 517.000 35.306 63.472 0.754 525.000 26.414 49.214 0.779 523.000 31.917 55.816 0.799 519.000 38.030 61.713 0.780 509.000 27.534 48.664 0.769 512.000 18.387 45.351 0.801 519.000 50.556 57.888 0.792 517.000 43.901 54.091 0.852 510.000 48.572 59.098 0.807 509.000 43.899 58.962 0.797 501.000 37.532 55.433 0.783 507.000 40.357 60.403 0.779 569.000 35.489 60.721 0.785 580.000 29.027 48.440 0.817 578.000 34.485 57.981 0.810 565.000 42.598 60.258 0.798 547.000 30.306 47.312 0.795 555.000 26.451 46.980 0.785 562.000 47.460 54.846 0.785 561.000 50.104 56.824 0.785 555.000 61.465 67.744 0.805 544.000 53.726 62.849 0.824 537.000 39.477 54.691 0.819 543.000 43.895 65.461 0.827 594.000 31.481 53.724 0.826 611.000 29.896 54.560 0.829 613.000 33.842 57.722 0.830 611.000 39.120 55.458 0.825 594.000 33.702 48.490 0.817 595.000 25.094 46.362
 
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'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Summary of Dendrogram
LabelHeight
12.68360093903695
23.45010434624810
33.49462244026447
43.81002388443957
53.84444859505235
64.02307071774782
74.31541666586206
84.74254804930852
95.16565068505411
105.43775404004263
115.68573662773786
125.85487053657039
136.32202989553197
147.0818832241149
157.15001545452875
167.53818928139692
177.64398398723878
187.75387116220021
197.91873190605667
208.17026382682958
218.42006429606043
228.88657740640343
238.91220237002537
249.02981643500039
259.12103831338205
269.20146577187764
2710.2211203397671
2810.5853836340681
2910.7696701584471
3010.8376696156994
3110.8635880706086
3211.1723528855832
3311.5266840851999
3414.8887021729892
3517.2231334292400
3617.9883519042991
3718.3047268619375
3818.7965400411813
3919.5653309502943
4020.8443791383316
4123.0173968537588
4224.6111718138985
4326.6301328390295
4427.7481017895351
4528.0438335878613
4628.247326017384
4731.0579806909072
4847.5334075996199
4949.3582113442747
5052.589329644168
5155.0050141045101
5256.5174414681639
5365.5434140673495
5475.2067027962923
55107.749790094624
56171.893523138693
57255.504315386055
58665.819492536056
591430.04846785453
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t1226338684tg6ca8cagl6455y/1jr4p1226338588.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t1226338684tg6ca8cagl6455y/1jr4p1226338588.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t1226338684tg6ca8cagl6455y/2ber81226338588.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/10/t1226338684tg6ca8cagl6455y/2ber81226338588.ps (open in new window)


 
Parameters (Session):
 
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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