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Q2

*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, 24 Nov 2008 13:17:22 -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/24/t1227557887zzlol9pc7o862cn.htm/, Retrieved Mon, 24 Nov 2008 20:18:07 +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/24/t1227557887zzlol9pc7o862cn.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 «
97.6 93.4 83.6 113.5 99.5 101.1 86.5 106.9 110.7 114.2 96 119.5 104.4 104.8 91 109.4 99.8 113.3 87.2 106.8 108.4 118.2 84.5 118.7 91.8 83.6 59.1 109 90.2 73.9 61.6 112.9 109.2 99.5 98.8 125.1 111.4 97.7 97.9 126.6 102.8 103 92.8 122.6 91.5 106.3 84.2 127.4 98.9 92.2 74.6 107.1 100.8 101.8 79.8 112 112.1 122.8 86.7 122.1 106.7 111.8 79.8 111.7 103.5 106.3 87 113.1 111.3 121.5 91.3 128.2 100.8 81.9 58.7 115.2 94.2 85.4 62.8 117.4 115.5 110.9 87.8 132 114.1 117.3 90.4 130.8 105 106.3 80.6 128 94 105.6 73.5 132.8 98.3 101.2 71.5 116.9 96 105.9 70.6 110.9 101.8 126.3 78.3 123.6 102.5 111.9 76 117.4 98.7 108.9 77.4 122.6 110.7 127.2 80.9 123.5 88.7 94.2 63.5 111.4 89.2 85.7 58 113.8 106.8 116.2 88.2 131.2 104.1 107.2 81.2 126.9 103.2 110.5 84.9 126.1 93.7 112 76.4 121.2 100.5 104.4 71.5 118.7 98.7 112 76.1 117.9 111.1 132.8 82.9 135.3 104.5 110.8 78.1 120.7 105 128.7 82 126.3 109.7 136.8 84.7 129.7 92.6 94.8 55.7 113.3 94.2 88.8 59.5 120.5 111.7 123.2 83.2 135.5 113.4 125.3 87.6 137.5 106.8 122.7 76.2 130.7 98 125.8 76.4 133.1 104.2 116.3 68.2 121.5 105.4 118.6 70 120.5 117.5 142.1 76.3 137 107.9 127.9 70.9 123.6 107 132 72.5 128.5 113.3 152.4 80.1 135 97.6 110.8 57.4 120.8 98.2 99.1 62.7 121.2 111.3 134.9 82.6 132.1 116 133.2 88.9 134.5 108.1 131 80.5 133.6 95.6 133.9 72.1 135.9 110.8 119.9 69.4 124.5
 
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'Herman Ole Andreas Wold' @ 193.190.124.10:1001


Summary of Dendrogram
LabelHeight
11.78605710994918
23.31209903233584
33.33766385365573
43.83536178215302
53.84447655734823
64.28018691180654
75.53714727996284
85.54325886715957
95.66215506675682
105.72276157112979
115.74891294072193
125.9514704065466
136.08111831820431
146.12943716828878
156.30728891628711
166.6475559418481
177.15891053163816
187.17656347585904
197.45393471120066
208.548684109265
218.59530480910621
228.68097720376029
238.93187523769623
248.94538987411951
259.63587048480831
2610.0300691030206
2710.6864570720117
2810.8780684608904
2911.2799630673671
3011.3394520284487
3111.3415166534287
3211.6815779087268
3311.9235061957463
3412.2633600615818
3512.8646803302686
3613.4026874421794
3713.5347892132223
3813.5370569844050
3914.2306922061872
4014.5626703246354
4114.8227320175029
4216.0442082255151
4317.4156919937939
4420.0002375155811
4521.0959265210519
4622.0269917840084
4722.035865847362
4822.8132078655976
4929.2972660426492
5029.5247764768785
5131.2522751339651
5231.9614721811981
5337.7467667346366
5452.9831239015886
5561.3029059992945
5683.0135386954929
5792.5527570801319
5893.9031599182346
59222.850909119604
60450.196400111336
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/24/t1227557887zzlol9pc7o862cn/11zev1227557836.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/24/t1227557887zzlol9pc7o862cn/11zev1227557836.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/24/t1227557887zzlol9pc7o862cn/25tce1227557836.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/24/t1227557887zzlol9pc7o862cn/25tce1227557836.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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