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hierarchical clustering various eda q2

*Unverified author*
R Software Module: rwasp_hierarchicalclustering.wasp (opens new window with default values)
Title produced by software: Hierarchical Clustering
Date of computation: Wed, 12 Nov 2008 11:07:33 -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/12/t12265133206lncslkmd9du89s.htm/, Retrieved Wed, 12 Nov 2008 18:08:42 +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/12/t12265133206lncslkmd9du89s.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 «
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 92.2 152.6 89.7 166.1 128.8 154.4 103.6 159.4 134.9 154.6 100 168.2 128.2 158 96.6 154.6 114.8
 
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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Summary of Dendrogram
LabelHeight
13.43365694267788
23.92428337406971
35.44334456010272
46.29603049547887
56.38905313798532
66.4643276916905
76.88331315574121
88.4823345842993
98.52056336165632
109.20326029187484
119.4884139875956
129.5827970864461
139.64782797933012
149.65453261426985
159.80510071340422
169.91665266105453
1710.1557865278865
1810.4599235178848
1910.5057127316522
2010.9571894206498
2111.3735314217756
2211.7961713539548
2311.8105025799616
2412.3309058630512
2512.8359134687778
2613.3157801123329
2713.7124045820179
2814.5771830084508
2914.9948236166537
3015.3143723345098
3115.7744724692083
3215.8324965218668
3315.9553431340328
3415.9740510896747
3517.7676672638813
3618.0335100339292
3718.3254110887979
3819.0153607500328
3921.175076601454
4021.7616583898476
4122.0047722096821
4222.0231884841217
4322.5438659939566
4426.7986988963492
4527.3794323998224
4628.5722657955422
4729.3010750020238
4835.3533111436116
4935.5158327254794
5035.8944851031859
5138.0751795829687
5242.7261202550327
5344.5971306721788
5447.8507642358316
5548.0217546294019
5659.4940857287324
5760.3324269612491
5869.7979100163632
5992.9084669644798
60106.916107478839
61109.337613127222
62219.424253944988
63265.806031770677
64957.730500296774
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t12265133206lncslkmd9du89s/1932v1226513251.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t12265133206lncslkmd9du89s/1932v1226513251.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t12265133206lncslkmd9du89s/27xe91226513251.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/12/t12265133206lncslkmd9du89s/27xe91226513251.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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