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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationTue, 11 Nov 2008 03:13:04 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/11/t1226398444mxdgwgif2w1kl0o.htm/, Retrieved Sun, 19 May 2024 10:10:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23269, Retrieved Sun, 19 May 2024 10:10:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Hierarchical Clustering] [Clusters] [2008-11-11 10:13:04] [270782e2502ae87124d0ebdcd1862d6a] [Current]
Feedback Forum
2008-11-19 16:19:10 [Bob Leysen] [reply] 
De grafiek is correct.

De gegevens zijn sterk verdeeld (in 2 stukken). Je kan blijven splitsen tot je bij 1 observatie komt.
Een dendrogram wordt meestal gebruikt voor niet tijdsreeksen. Vb. als er verschillende producten zijn kan je zien welke samenhoren.
2008-11-21 15:36:34 [Matthieu Blondeau] [reply] 
In deze grafiek kan men 2 grote delen onderscheiden. Dit wil zeggen dat gelijke objecten in verschillende groepen worden verdeeld. Hierdoor ontstaan subgroepen welke elk hun eigen gedeelde kenmerken bevatten.
2008-11-23 17:46:59 [Wim Golsteyn] [reply] 
Dit was eigenlijk simpeler dan ik had gedacht: de grafiek maakt een onderverdeling van elke cluster tot op het laagste niveau van 1 enkel punt.
2008-11-24 20:09:56 [Michaël De Kuyer] [reply] 
Zoals hierboven reeds is vermeld, worden de data opgedeeld in groepen en subgroepen. Deze methode wordt niet vaak toegepast op tijdreeksen, eerder op verwerkingen van marktonderzoeken.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
517	22780	2218
525	17351	1855
523	21382	2187
519	24561	1852
509	17409	1570
512	11514	1851
519	31514	1954
517	27071	1828
510	29462	2251
509	26105	2277
501	22397	2085
507	23843	2282
569	21705	2266
580	18089	1878
578	20764	2267
565	25316	2069
547	17704	1746
555	15548	2299
562	28029	2360
561	29383	2214
555	36438	2825
544	32034	2355
537	22679	2333
543	24319	3016
594	18004	2155
611	17537	2172
613	20366	2150
611	22782	2533
594	19169	2058
595	13807	2160
591	29743	2259
589	25591	2498
584	29096	2695
573	26482	2799
567	22405	2945
569	27044	2930
621	17970	2318
629	18730	2540
628	19684	2570
612	19785	2669
595	18479	2450
597	10698	2842
593	31956	3439
590	29506	2677
580	34506	2979
574	27165	2257
573	26736	2842
573	23691	2546
620	18157	2455
626	17328	2293
620	18205	2379
588	20995	2478
566	17382	2054
557	9367	2272
561	31124	2351
549	26551	2271
532	30651	2542
526	25859	2304
511	25100	2194
499	25778	2722
555	20418	2395
565	18688	2146
542	20424	1894
527	24776	2548
510	19814	2087
514	12738	2063
517	31566	2481
508	30111	2476
493	30019	2212
490	31934	2834
469	25826	2148
478	26835	2598

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23269&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23269&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23269&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Summary of Dendrogram
LabelHeight
189.888820216977
2101.049492824061
3142.330601066672
4154.356729688083
5168.683134900914
6169.333989500041
7199.934989434066
8255.337032175123
9257.085588860986
10257.614052411742
11262.840753087169
12268.806621942243
13279.973213004387
14291.28165064075
15305.36044275577
16311.698572341934
17313.020766084297
18315.576298752987
19325.584511759367
20335.687354542884
21378.866754432308
22380.04488053044
23394.564128418664
24410.438789589873
25424.730272516777
26427.940320764412
27429.721799349890
28442.861152055585
29462.817458616245
30490.956176300223
31492.297674176915
32570.834639871124
33571.94797735281
34601.061586932748
35651.092927315295
36654.31567305086
37718.069228092203
38772.427627741678
39781.23264851462
40865.092542845094
41898.939887466432
42919.067738209707
43937.11067051689
44953.444336516843
45955.024307338376
46970.57147264558
471076.44368175952
481286.53099457417
491375.44652925420
501405.77258381639
511433.59897761797
521566.05436647053
531795.01582037278
541866.93467542671
551938.28919410907
561995.70189279349
572011.48297883199
582207.16223636115
592685.97807111100
603976.52371804947
614028.98411990258
624545.55088286661
637099.5090708722
647920.33237167446
659026.09243893818
6613662.1615883572
6721195.0416999384
6822130.2240879234
6946113.303184552
7077865.9031322886
71220410.836013535

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 89.888820216977 \tabularnewline
2 & 101.049492824061 \tabularnewline
3 & 142.330601066672 \tabularnewline
4 & 154.356729688083 \tabularnewline
5 & 168.683134900914 \tabularnewline
6 & 169.333989500041 \tabularnewline
7 & 199.934989434066 \tabularnewline
8 & 255.337032175123 \tabularnewline
9 & 257.085588860986 \tabularnewline
10 & 257.614052411742 \tabularnewline
11 & 262.840753087169 \tabularnewline
12 & 268.806621942243 \tabularnewline
13 & 279.973213004387 \tabularnewline
14 & 291.28165064075 \tabularnewline
15 & 305.36044275577 \tabularnewline
16 & 311.698572341934 \tabularnewline
17 & 313.020766084297 \tabularnewline
18 & 315.576298752987 \tabularnewline
19 & 325.584511759367 \tabularnewline
20 & 335.687354542884 \tabularnewline
21 & 378.866754432308 \tabularnewline
22 & 380.04488053044 \tabularnewline
23 & 394.564128418664 \tabularnewline
24 & 410.438789589873 \tabularnewline
25 & 424.730272516777 \tabularnewline
26 & 427.940320764412 \tabularnewline
27 & 429.721799349890 \tabularnewline
28 & 442.861152055585 \tabularnewline
29 & 462.817458616245 \tabularnewline
30 & 490.956176300223 \tabularnewline
31 & 492.297674176915 \tabularnewline
32 & 570.834639871124 \tabularnewline
33 & 571.94797735281 \tabularnewline
34 & 601.061586932748 \tabularnewline
35 & 651.092927315295 \tabularnewline
36 & 654.31567305086 \tabularnewline
37 & 718.069228092203 \tabularnewline
38 & 772.427627741678 \tabularnewline
39 & 781.23264851462 \tabularnewline
40 & 865.092542845094 \tabularnewline
41 & 898.939887466432 \tabularnewline
42 & 919.067738209707 \tabularnewline
43 & 937.11067051689 \tabularnewline
44 & 953.444336516843 \tabularnewline
45 & 955.024307338376 \tabularnewline
46 & 970.57147264558 \tabularnewline
47 & 1076.44368175952 \tabularnewline
48 & 1286.53099457417 \tabularnewline
49 & 1375.44652925420 \tabularnewline
50 & 1405.77258381639 \tabularnewline
51 & 1433.59897761797 \tabularnewline
52 & 1566.05436647053 \tabularnewline
53 & 1795.01582037278 \tabularnewline
54 & 1866.93467542671 \tabularnewline
55 & 1938.28919410907 \tabularnewline
56 & 1995.70189279349 \tabularnewline
57 & 2011.48297883199 \tabularnewline
58 & 2207.16223636115 \tabularnewline
59 & 2685.97807111100 \tabularnewline
60 & 3976.52371804947 \tabularnewline
61 & 4028.98411990258 \tabularnewline
62 & 4545.55088286661 \tabularnewline
63 & 7099.5090708722 \tabularnewline
64 & 7920.33237167446 \tabularnewline
65 & 9026.09243893818 \tabularnewline
66 & 13662.1615883572 \tabularnewline
67 & 21195.0416999384 \tabularnewline
68 & 22130.2240879234 \tabularnewline
69 & 46113.303184552 \tabularnewline
70 & 77865.9031322886 \tabularnewline
71 & 220410.836013535 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23269&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]89.888820216977[/C][/ROW]
[ROW][C]2[/C][C]101.049492824061[/C][/ROW]
[ROW][C]3[/C][C]142.330601066672[/C][/ROW]
[ROW][C]4[/C][C]154.356729688083[/C][/ROW]
[ROW][C]5[/C][C]168.683134900914[/C][/ROW]
[ROW][C]6[/C][C]169.333989500041[/C][/ROW]
[ROW][C]7[/C][C]199.934989434066[/C][/ROW]
[ROW][C]8[/C][C]255.337032175123[/C][/ROW]
[ROW][C]9[/C][C]257.085588860986[/C][/ROW]
[ROW][C]10[/C][C]257.614052411742[/C][/ROW]
[ROW][C]11[/C][C]262.840753087169[/C][/ROW]
[ROW][C]12[/C][C]268.806621942243[/C][/ROW]
[ROW][C]13[/C][C]279.973213004387[/C][/ROW]
[ROW][C]14[/C][C]291.28165064075[/C][/ROW]
[ROW][C]15[/C][C]305.36044275577[/C][/ROW]
[ROW][C]16[/C][C]311.698572341934[/C][/ROW]
[ROW][C]17[/C][C]313.020766084297[/C][/ROW]
[ROW][C]18[/C][C]315.576298752987[/C][/ROW]
[ROW][C]19[/C][C]325.584511759367[/C][/ROW]
[ROW][C]20[/C][C]335.687354542884[/C][/ROW]
[ROW][C]21[/C][C]378.866754432308[/C][/ROW]
[ROW][C]22[/C][C]380.04488053044[/C][/ROW]
[ROW][C]23[/C][C]394.564128418664[/C][/ROW]
[ROW][C]24[/C][C]410.438789589873[/C][/ROW]
[ROW][C]25[/C][C]424.730272516777[/C][/ROW]
[ROW][C]26[/C][C]427.940320764412[/C][/ROW]
[ROW][C]27[/C][C]429.721799349890[/C][/ROW]
[ROW][C]28[/C][C]442.861152055585[/C][/ROW]
[ROW][C]29[/C][C]462.817458616245[/C][/ROW]
[ROW][C]30[/C][C]490.956176300223[/C][/ROW]
[ROW][C]31[/C][C]492.297674176915[/C][/ROW]
[ROW][C]32[/C][C]570.834639871124[/C][/ROW]
[ROW][C]33[/C][C]571.94797735281[/C][/ROW]
[ROW][C]34[/C][C]601.061586932748[/C][/ROW]
[ROW][C]35[/C][C]651.092927315295[/C][/ROW]
[ROW][C]36[/C][C]654.31567305086[/C][/ROW]
[ROW][C]37[/C][C]718.069228092203[/C][/ROW]
[ROW][C]38[/C][C]772.427627741678[/C][/ROW]
[ROW][C]39[/C][C]781.23264851462[/C][/ROW]
[ROW][C]40[/C][C]865.092542845094[/C][/ROW]
[ROW][C]41[/C][C]898.939887466432[/C][/ROW]
[ROW][C]42[/C][C]919.067738209707[/C][/ROW]
[ROW][C]43[/C][C]937.11067051689[/C][/ROW]
[ROW][C]44[/C][C]953.444336516843[/C][/ROW]
[ROW][C]45[/C][C]955.024307338376[/C][/ROW]
[ROW][C]46[/C][C]970.57147264558[/C][/ROW]
[ROW][C]47[/C][C]1076.44368175952[/C][/ROW]
[ROW][C]48[/C][C]1286.53099457417[/C][/ROW]
[ROW][C]49[/C][C]1375.44652925420[/C][/ROW]
[ROW][C]50[/C][C]1405.77258381639[/C][/ROW]
[ROW][C]51[/C][C]1433.59897761797[/C][/ROW]
[ROW][C]52[/C][C]1566.05436647053[/C][/ROW]
[ROW][C]53[/C][C]1795.01582037278[/C][/ROW]
[ROW][C]54[/C][C]1866.93467542671[/C][/ROW]
[ROW][C]55[/C][C]1938.28919410907[/C][/ROW]
[ROW][C]56[/C][C]1995.70189279349[/C][/ROW]
[ROW][C]57[/C][C]2011.48297883199[/C][/ROW]
[ROW][C]58[/C][C]2207.16223636115[/C][/ROW]
[ROW][C]59[/C][C]2685.97807111100[/C][/ROW]
[ROW][C]60[/C][C]3976.52371804947[/C][/ROW]
[ROW][C]61[/C][C]4028.98411990258[/C][/ROW]
[ROW][C]62[/C][C]4545.55088286661[/C][/ROW]
[ROW][C]63[/C][C]7099.5090708722[/C][/ROW]
[ROW][C]64[/C][C]7920.33237167446[/C][/ROW]
[ROW][C]65[/C][C]9026.09243893818[/C][/ROW]
[ROW][C]66[/C][C]13662.1615883572[/C][/ROW]
[ROW][C]67[/C][C]21195.0416999384[/C][/ROW]
[ROW][C]68[/C][C]22130.2240879234[/C][/ROW]
[ROW][C]69[/C][C]46113.303184552[/C][/ROW]
[ROW][C]70[/C][C]77865.9031322886[/C][/ROW]
[ROW][C]71[/C][C]220410.836013535[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23269&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23269&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of Dendrogram
LabelHeight
189.888820216977
2101.049492824061
3142.330601066672
4154.356729688083
5168.683134900914
6169.333989500041
7199.934989434066
8255.337032175123
9257.085588860986
10257.614052411742
11262.840753087169
12268.806621942243
13279.973213004387
14291.28165064075
15305.36044275577
16311.698572341934
17313.020766084297
18315.576298752987
19325.584511759367
20335.687354542884
21378.866754432308
22380.04488053044
23394.564128418664
24410.438789589873
25424.730272516777
26427.940320764412
27429.721799349890
28442.861152055585
29462.817458616245
30490.956176300223
31492.297674176915
32570.834639871124
33571.94797735281
34601.061586932748
35651.092927315295
36654.31567305086
37718.069228092203
38772.427627741678
39781.23264851462
40865.092542845094
41898.939887466432
42919.067738209707
43937.11067051689
44953.444336516843
45955.024307338376
46970.57147264558
471076.44368175952
481286.53099457417
491375.44652925420
501405.77258381639
511433.59897761797
521566.05436647053
531795.01582037278
541866.93467542671
551938.28919410907
561995.70189279349
572011.48297883199
582207.16223636115
592685.97807111100
603976.52371804947
614028.98411990258
624545.55088286661
637099.5090708722
647920.33237167446
659026.09243893818
6613662.1615883572
6721195.0416999384
6822130.2240879234
6946113.303184552
7077865.9031322886
71220410.836013535


Figures (Output of Computation)

Input Parameters & R Code

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')
}