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Q2 Hierarchical Cluster Average

*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: Tue, 11 Nov 2008 05:35:40 -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/11/t1226407000muj3g3yesbfx04f.htm/, Retrieved Tue, 11 Nov 2008 12:36:43 +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/11/t1226407000muj3g3yesbfx04f.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 «
604.4 882.5 1.1663 883.9 789.6 1.1372 527.9 773.3 1.1139 756.2 804.3 1.1222 812.9 817.8 1.1692 655.6 836.7 1.1702 707.6 721.8 1.2286 612.6 760.8 1.2613 659.2 841.4 1.2646 833.4 1045.6 1.2262 727.8 949.2 1.1985 797.2 850.1 1.2007 753 957.4 1.2138 762 851.8 1.2266 613.7 913.9 1.2176 759.2 888 1.2218 816.4 973.8 1.249 736.8 927.6 1.2991 680.1 833 1.3408 736.5 879.5 1.3119 637.2 797.3 1.3014 801.9 834.5 1.3201 772.3 735.1 1.2938 897.3 835 1.2694 792.1 892.8 1.2165 826.8 697.2 1.2037 666.8 821.1 1.2292 906.6 732.7 1.2256 871.4 797.6 1.2015 891 866.3 1.1786 739.2 826.3 1.1856 833.6 778.6 1.2103 715.6 779.2 1.1938 871.6 951 1.202 751.6 692.3 1.2271 1005.5 841.4 1.277 681.2 857.3 1.265 837.3 760.7 1.2684 674.7 841.2 1.2811 806.3 810.3 1.2727 860.2 1007.4 1.2611 689.8 931.3 1.2881 691.6 931.2 1.3213 682.6 855.8 1.2999 800.1 858.4 1.3074 1023.7 925.9 1.3242 733.5 930.7 1.3516 875.3 1037.6 1.3511 770.2 979.2 1.3419 1005.7 942.6 1.3716 982.3 843.9 1.3622 742.9 854.3 1.3896 974.2 1029.8 1.4227 822.3 944 1.4684 773.2 856.4 1.457 750.9 1059.4 1.4718 708 959.3 1.4748 690 941.5 1.5527 652.8 1026.4 1.575 620.7 921.3 1.5557 461.9 968 1.5553
 
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'George Udny Yule' @ 72.249.76.132


Summary of Dendrogram
LabelHeight
11.80308131818846
22.05212524227931
34.52799693573216
45.92105660841032
58.79268928656069
69.8185316667005
79.9910315908819
810.1918747838658
910.3157453228864
1012.1100406341185
1114.8409613735095
1218.2784948945475
1319.7218693029680
1420.1303819108781
1520.5513785891066
1621.3795120252344
1723.3344650472215
1824.2393918655151
1924.5538641920167
2024.8181836264885
2127.7686227532084
2227.802949835584
2327.8863816982830
2430.3792385743948
2530.4155678660795
2631.9278600072100
2733.764746408051
2835.4005647875149
2935.8870233745505
3037.4174597019281
3141.3437634238151
3244.01603807716
3344.6602794432746
3447.5429747585277
3548.9535965371186
3649.7182801158495
3750.2070545339706
3854.7592854878775
3959.5134700365525
4060.8907419738382
4161.0218606657251
4274.016548446279
4375.7861385306848
4477.9283937768267
4582.8549314494033
4687.8180575656813
4788.2393290723047
4895.2330884341146
4998.561072181484
50103.501790565381
51115.524038508644
52126.147513111894
53138.056464791623
54143.278451044256
55145.233031943145
56177.722292245907
57190.882783709237
58205.582793136877
59239.124297653393
60310.344565226991
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226407000muj3g3yesbfx04f/1ftm01226406939.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226407000muj3g3yesbfx04f/1ftm01226406939.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226407000muj3g3yesbfx04f/2ibzz1226406939.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226407000muj3g3yesbfx04f/2ibzz1226406939.ps (open in new window)


 
Parameters (Session):
par1 = average ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
 
Parameters (R input):
par1 = average ; 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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