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Hierarchical clustering

*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 08:09:47 -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/t1226416238r8f1u0rhf1osqah.htm/, Retrieved Tue, 11 Nov 2008 15:10:38 +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/t1226416238r8f1u0rhf1osqah.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 «
11008.9 3202.1 10230.4 3467.9 9996.6 3650.2 9221 3256.6 9419.5 2805.1 9428.6 3711.1 11958.8 3957.5 10934.5 3597.7 12594.6 3941.3 10986 4181.1 11890.6 3905.4 11724.6 4346.5 10871.7 3546.9 11180.9 3646.6 11835.7 3208.7 11163.2 3918.8 11542.2 3402 11240.9 3531.8 13093.7 3661.1 12107.1 3976 11180.2 3073.9 10762.3 3510.2 12035.7 3419.2 11340.4 3882.9 12112 3532.8 11266.8 3630.4 10875.2 3693.1 9542.7 3519.9 9897.3 2622.9 9227.7 3376.1 11672.1 3130.8 10571.9 3057.9 12385.7 3487.5 10774.4 3646.7 11405.6 3349.7 10392.8 3585.5 9830.9 3044.2 9920.2 3007.7 11025.1 3266 9884.9 3545 10853.8 3351.5 10174.5 3295.6 12252.6 3606.8 11395.4 3390.3 11839.4 3419.5 10760.2 3531.9 11669.1 3829.5 10570.1 3738.7 11601.4 3505.1 10536 3477 11178.4 3845.3 9902.6 3338.3 9516.4 2566.6 8889 3264.4 12102.8 3658.5 10837.3 3452.4 12989 3954 11624.1 4045.1 11610.2 3460.1 10509 3660.5 10205.5 3454.1 10984.9 3584.9 11356.2 3412.8 10649.1 3819.9 11307.1 3418 10855.7 3409.2 12648.6 3349.5 11677.4 3643.5 11947.2 3423.4 10760.2 3673.3 11714.1 3242.8 10046.2 3645.2 12192.5 3277.2 10772.8 3421.3 11268.8 3833 9987.7 3531.4 9097.4 2606.3 8638.7 3219.2 12639.8 3643.8 11063.7 3552.3 13040.1 3686.4 11855.7 3787.7 11687.3 3281.6 10684.5 3392.7 11191.7 3669.3 11337.4 3550 11391.9 3191.5 10478 3681.9 11793.1 3512.7 11123.9 3519.1 13933.2 3970.7 12909.3 4283.2 12778.1 3601.2 11339.9 4046.2 11810.3 3610 10462.2 3824.9 13698.4 4172.1 12733.5 4793.1 11956.6 3956.2 10519.2 3977.7 10723.8 3142.7 10414.9 3983.4 13938.9 3884.3 12476.8 4152.9 13979.8 3892.2 12384.6 4286.1 13807.4 3613 12266.7 4348.1 12973.9 3730.5 12919.9 3949.3 12509.8 3481.3 11497.3 4166.7 12934.1 3649.5 12142 4217.9 14908.3 4215.2 13919.4 4528.2 13772.1 4066.6 12656.8 4232.2 13012.6 4196.8 12034.1 4470.9 14049.9 4536.6 13199.7 5121.2 11816.5 4441.6 10881.3 4170.8 11593.2 3548.3 11301.2 4398.6 14466.2 4735.9 13643.9 4491.4 13615.9 4130.6 12517 4251.8 14733.9 4356.2 13981.1 4901.9 13880.7 4159.6 14275.7 4745.2 13527.5 3988 13435 4666.9 13584 4167.8 13565.7 4210.4 16170.2 4902.2 16216.3 5273.6 13260.6 3909.4 12970 4095.3 14741.9 4697.6 14079.9 4610.1 15486.5 4308.9 14235 4718.1 13154.5 4420.4 12213.4 4185.5 12621.2 3544.2 12581 4314.7 15031.6 4433 14130.4 4422.6 15452.4 4479.7 14210.8 5059.2 15428 4533.2 14378.5 5043.6 13105.9 4237.5 13142.8 4436.6 14716.8 4207.4 13714.7 4922.6 14180 4394 13621.9 4454.8 16202.2 5148.4 15379.8 5058.7 14392.4 4202.2 13306.3 4768.9 15140.6 4682.5 14391.2 5171.8 15960.1 4884.3 14909.9 4989.3 14351.3 5288.9 14025.4 5202.1 13230.2 4505.2 12951.2 4838.4 15202.1 4611.5 14344.3 4876.5 17157.3 5081.1 16213.3 5845.3 16159.1 4523.1 15544.5 5686.3 13405.7 4412.8 14750.6 4753.8 17224.7 4647.4 17292.7 6620.4 17338.4 4778.6 17568.5 5597.2 17370.6 4495.3 17930.8 5643.5 18817.8 4633.5 18644.7 6357.3 16593.2 4360.5 16694.8 5909.1 17979.5 4517.9 17242.8 6165.8
 
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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Summary of Dendrogram
LabelHeight
1167.267151586915
2177.848278034960
3178.393553695194
4191.059388672737
5204.36959167156
6220.051448529657
7229.897955623794
8281.404459808298
9292.130689931749
10295.280442969052
11296.479105503238
12298.421832311243
13306.318951421553
14313.408599116234
15343.965245337374
16354.479773753031
17356.447780186664
18363.813207566740
19371.521345281803
20372.512040073874
21374.598117987797
22388.851604085672
23391.705220797477
24409.701073955146
25416.102138903418
26424.588318256638
27427.46047770525
28428.642298426088
29440.584032847311
30447.916967751837
31463.358079674888
32491.762361308793
33510.876726813818
34524.680874437023
35524.89605637688
36530.219341405046
37534.104465437239
38536.247825170414
39541.171488532055
40562.537438754081
41594.96520066303
42596.822151063447
43603.828170922822
44610.450833401019
45614.011034102808
46621.76896834757
47627.546420593727
48630.832101275767
49643.486977335205
50646.139017549629
51648.692084120039
52699.618395984554
53717.871304622214
54756.836105111272
55768.998335498849
56797.238847523124
57842.298444733219
58860.465600706966
59861.197282856837
60874.915167316237
61891.989047017954
62898.325030264659
63915.443875942157
64931.02517688836
65943.707438775386
66952.53886534881
67972.38075875657
681005.48866229312
691005.81021072566
701033.06462527763
711036.04336781816
721069.75499064038
731094.77974953869
741141.88801990388
751174.27135705509
761185.71768984021
771334.29445026201
781366.01553797898
791373.81700018598
801374.67180446825
811436.68816727918
821554.59099444195
831672.39149722785
841761.86257977176
851822.79806616092
861943.97511815352
872048.62639102400
882106.01197290044
892146.54180019863
902169.58108859752
912799.14800787668
923855.89357347943
934751.53615791777
944904.02946259502
958947.8030471172
9614441.7250912071
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226416238r8f1u0rhf1osqah/12xxb1226416181.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226416238r8f1u0rhf1osqah/12xxb1226416181.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226416238r8f1u0rhf1osqah/2lpkh1226416181.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226416238r8f1u0rhf1osqah/2lpkh1226416181.ps (open in new window)


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