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Q2 Hierarchical Cluster single

*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 05:32:12 -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/t1226406790wt52ipvdiim9lcb.htm/, Retrieved Tue, 11 Nov 2008 12:33:13 +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/t1226406790wt52ipvdiim9lcb.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'Gwilym Jenkins' @ 72.249.127.135


Summary of Dendrogram
LabelHeight
11.80308131818846
22.05212524227931
34.52799693573216
45.92105660841032
58.79268928656069
69.8185316667005
79.9910315908819
810.1918747838658
910.2053913771105
1012.1100406341185
1114.8409613735095
1215.5012990504022
1316.2930738769577
1416.6003118476731
1517.8469172284740
1618.2784948945475
1719.2636073724524
1819.3588078044595
1919.9978191513475
2022.2289527798769
2123.3344650472215
2224.2393918655151
2324.5538641920167
2424.8144250324282
2525.3149376536858
2626.0001161014716
2726.5005704483885
2827.7686227532084
2927.802949835584
3028.2441430388674
3130.3792385743948
3231.9278600072100
3332.7483225782635
3433.2483086500652
3533.764746408051
3637.9816431034783
3741.8351992197958
3842.3065015977450
3942.6570697541451
4044.01603807716
4145.4925775309555
4245.4964391495643
4346.514606635013
4447.5429747585277
4547.732327897977
4649.7951902191367
4752.9740502722795
4855.2032620993543
4957.9548204297107
5058.8803884498056
5161.2609811752962
5264.362288539874
5368.5000705320076
5482.489677378506
5585.4647214459861
5685.61753165538
5786.4377939783287
5886.8876288089393
5992.7151153329919
60161.152611028460
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226406790wt52ipvdiim9lcb/17s3r1226406730.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226406790wt52ipvdiim9lcb/17s3r1226406730.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226406790wt52ipvdiim9lcb/29rip1226406730.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226406790wt52ipvdiim9lcb/29rip1226406730.ps (open in new window)


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