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Hierarchical Clustering Bel20, DJI, LBO

*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, 15 Dec 2008 04:20:36 -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/Dec/15/t1229340119tvomos71b1m1vs8.htm/, Retrieved Mon, 15 Dec 2008 12:22:03 +0100
 
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/Dec/15/t1229340119tvomos71b1m1vs8.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},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
2120.88 9682.35 29.08 2174.56 9762.12 28.76 2196.72 10124.63 29.59 2350.44 10540.05 30.70 2440.25 10601.61 30.52 2408.64 10323.73 32.67 2472.81 10418.40 33.19 2407.60 10092.96 37.13 2454.62 10364.91 35.54 2448.05 10152.09 37.75 2497.84 10032.80 41.84 2645.64 10204.59 42.94 2756.76 10001.60 49.14 2849.27 10411.75 44.61 2921.44 10673.38 40.22 2981.85 10539.51 44.23 3080.58 10723.78 45.85 3106.22 10682.06 53.38 3119.31 10283.19 53.26 3061.26 10377.18 51.80 3097.31 10486.64 55.30 3161.69 10545.38 57.81 3257.16 10554.27 63.96 3277.01 10532.54 63.77 3295.32 10324.31 59.15 3363.99 10695.25 56.12 3494.17 10827.81 57.42 3667.03 10872.48 63.52 3813.06 10971.19 61.71 3917.96 11145.65 63.01 3895.51 11234.68 68.18 3801.06 11333.88 72.03 3570.12 10997.97 69.75 3701.61 11036.89 74.41 3862.27 11257.35 74.33 3970.10 11533.59 64.24 4138.52 11963.12 60.03 4199.75 12185.15 59.44 4290.89 12377.62 62.50 4443.91 12512.89 55.04 4502.64 12631.48 58.34 4356.98 12268.53 61.92 4591.27 12754.80 67.65 4696.96 13407.75 67.68 4621.40 13480.21 70.30 4562.84 13673.28 75.26 4202.52 13239.71 71.44 4296.49 13557.69 76.36 4435.23 13901.28 81.71 4105.18 13200.58 92.60 4116.68 13406.97 90.60 3844.49 12538.12 92.23 3720.98 12419.57 94.09 3674.40 12193.88 102.79 3857.62 12656.63 109.65 3801.06 12812.48 124.05 3504.37 12056.67 132.69 3032.60 11322.38 135.81 3047.03 11530.75 116.07 2962.34 11114.08 101.42
 
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'Gwilym Jenkins' @ 72.249.127.135


Summary of Dendrogram
LabelHeight
129.4321507878713
240.701953270083
349.5446152472707
456.547136974386
571.6445657394903
687.1864215345485
796.1503910548473
898.5918719237757
9104.721676839134
10107.023259621448
11108.882974334834
12110.481012848362
13120.500926967387
14127.549412385945
15129.995701852022
16131.291050710351
17132.377078831647
18134.708989413518
19146.923875187118
20158.676088620813
21185.407242063833
22185.797405794591
23209.799784079966
24218.128842881728
25218.855835483981
26220.523910268251
27227.546819680306
28228.122067623844
29231.497374715136
30243.782913298630
31246.334052108448
32254.730112581503
33256.679972858433
34261.361654800394
35329.763785016267
36339.103976603738
37353.502886964272
38362.030747675153
39393.97368838804
40414.573526650052
41431.721814997212
42437.30479462004
43469.55655432689
44560.401764602405
45603.429123287684
46618.783100628122
47808.909084629662
481040.04482003274
491201.48586749047
501204.88180138086
511316.75254541482
521621.33359797309
531739.58664922588
542576.13896143818
552620.11850888589
566291.83355832964
577229.9208078198
5812361.8215545781
5946096.3952523531
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/15/t1229340119tvomos71b1m1vs8/1zosh1229340033.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/15/t1229340119tvomos71b1m1vs8/1zosh1229340033.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/15/t1229340119tvomos71b1m1vs8/2wd7q1229340033.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/15/t1229340119tvomos71b1m1vs8/2wd7q1229340033.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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