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Q2 Hierarchical Cluster Ward

*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 05:30:04 -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/t12264066651cgmnqmnmq1960v.htm/, Retrieved Tue, 11 Nov 2008 12:31:07 +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/11/t12264066651cgmnqmnmq1960v.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 time3 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
912.1100406341185
1013.153299991119
1114.8409613735095
1218.2784948945475
1322.2289527798769
1423.0229818483905
1523.3344650472215
1623.9096127856506
1724.2393918655151
1824.5538641920167
1927.7686227532084
2027.802949835584
2129.0542312906118
2230.3792385743948
2331.9278600072100
2432.6340692427732
2533.764746408051
2644.01603807716
2746.4926546746156
2847.5429747585277
2948.2921237883491
3048.5744700962832
3152.1982017231678
3257.6750894334328
3357.8105327173876
3462.8859677923717
3563.5036351292274
3664.4234420484223
3765.8858157066221
3882.3958819161652
3982.8768320976705
4087.340085182063
41103.501790565381
42117.009067808070
43123.305139395024
44130.351431687277
45141.177131547455
46160.903756066627
47174.887817838757
48180.421639021395
49197.401471420562
50231.280945140610
51232.258669832457
52288.651833982406
53310.712496208711
54336.878154464803
55421.693133088249
56640.357071732618
57688.354957497548
581054.20091656874
591652.17885460388
602310.68590499412
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t12264066651cgmnqmnmq1960v/1fq5f1226406600.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t12264066651cgmnqmnmq1960v/1fq5f1226406600.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t12264066651cgmnqmnmq1960v/2e7o51226406600.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t12264066651cgmnqmnmq1960v/2e7o51226406600.ps (open in new window)


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