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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 computationThu, 13 Nov 2008 18:11:20 -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/14/t1226625233ax7v76n8w6ptzgp.htm/, Retrieved Sun, 19 May 2024 10:47:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24898, Retrieved Sun, 19 May 2024 10:47:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsHierarchical clustering own time series
Estimated Impact261

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] [Hierarchical clus...] [2008-11-14 01:11:20] [9f72e095d5529918bf5b0810c01bf6ce] [Current]
Feedback Forum
2008-11-15 13:58:50 [Maarten Van Gucht] [reply] 
De studente heeft geen grafiek gekopieerd in het word document of geen conclusie gemaakt. De link geeft wel een juiste weergave weer van de hierarchical clustering. Een dendogram is een tijdreeks die opgesplitst is in 2 delen. je bekomt dan een linker en een rechtercluster. De linkercluster heeft de eerste groep maanden en de rechtercluster heeft de rest van de maanden. Een dendogram gebruikten we exploratief (verkennend)
2008-11-19 13:02:57 [Sam De Cuyper] [reply] 
Ook hier weer enkel de berekening zonder interpretatie. Bij hierarchical clustering begint men bovenaan vanuit het knooppunt. Van daaruit ontspringen 2 aparte takken die perioden bevatten die gelijkaardig zijn. Je zou kunnen zeggen dat de gegevens links anders zijn dan de gegevens rechts, die daarop volgen. Bij de clustering worden de gegevens telkens naar beneden toe opgesplitst tot ze helemaal onderaan de periodes allemaal apart weergeeft. We gebruiken deze methode louter als exploratief instrument.
2008-11-23 12:55:26 [An Knapen] [reply] 
Een dendrogram is een boomstructuur-diagram. Deze wordt gebruikt om weer te geven hoe en waar de clusters zich bevinden ofwel zijn geplaatst. We kunnen duidelijk twee grote groepen onderscheiden waarde de ene groep lage cijfers bevat en de andere groep de hoge cijfers.
2008-11-23 14:56:41 [c97d2ae59c98cf77a04815c1edffab5a] [reply] 
des student heeft geen grafieken weergegeven, noch een conclusie gevormd.
dmv een dendogram Kunnen we nagaan of er in periodes groepen gemaakt kunnen worden die gelijkaardig zijn? De tijdsreeks wordt allereerst opgesplitst in 2 delen (2 vertakkingen vanuit 1 knooppunt), elke vertakking/cluster geeft periodes weer de gelijkaardig zijn.
bij deze tijdsreeks zitten alle periodes t.e.m. 31 in de eerste cluster en in de tweede periodes de volgende. We kunnen hier dus wel een patroon vast stellen, wat verder onderzocht ka worden.
2008-11-24 02:39:26 [Anna Hayan] [reply] 
Er ontbreekt een grafiek en de conclusie. Dendograf geef weer of er in periodes groepen gemaakt kunnen worden die gelijkaardig zijn. De tijdsreeks wordt opgesplitst in 2 vertakkingen vanuit 1 punt Elke vertakking of cluster cluster geeft periodes aan die min of meer op elkaar lijken.

2008-11-24 02:39:59 [Anna Hayan] [reply] 
Een correctie van een typfout het moet dendogram zijn, mijn excuses
2008-11-24 22:31:57 [Jessica Alves Pires] [reply] 
Juiste berekening, geen interpretatie. De theorie is hierboven goed uitgelegd. Bij hierarchical clustering begint men boven vanuit het knooppunt, daaruit ontspringen 2 takken die perioden bevatten die gelijkaardig zijn. We clusteren de reeksen.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,1372	9924	789,6
1,1139	10371	773,3
1,1222	10846	804,3
1,1692	10413	817,8
1,1702	10709	836,7
1,2286	10662	721,8
1,2613	10570	760,8
1,2646	10297	841,4
1,2262	10635	1045,6
1,1985	10872	949,2
1,2007	10296	850,1
1,2138	10383	957,4
1,2266	10431	851,8
1,2176	10574	913,9
1,2218	10653	888
1,249	10805	973,8
1,2991	10872	927,6
1,3408	10625	833
1,3119	10407	879,5
1,3014	10463	797,3
1,3201	10556	834,5
1,2938	10646	735,1
1,2694	10702	835
1,2165	11353	892,8
1,2037	11346	697,2
1,2292	11451	821,1
1,2256	11964	732,7
1,2015	12574	797,6
1,1786	13031	866,3
1,1856	13812	826,3
1,2103	14544	778,6
1,1938	14931	779,2
1,202	14886	951
1,2271	16005	692,3
1,277	17064	841,4
1,265	15168	857,3
1,2684	16050	760,7
1,2811	15839	841,2
1,2727	15137	810,3
1,2611	14954	1007,4
1,2881	15648	931,3
1,3213	15305	931,2
1,2999	15579	855,8
1,3074	16348	858,4
1,3242	15928	925,9
1,3516	16171	930,7
1,3511	15937	1035,6
1,3419	15713	979,2
1,3716	15594	942,6
1,3622	15683	843,9
1,3896	16438	854,3
1,4227	17032	1029,8
1,4684	17696	944
1,457	17745	856,4
1,4718	19394	1059,4
1,4748	20148	959,3
1,5527	20108	941,5
1,575	18584	1026,4
1,5557	18441	921,3
1,5553	18391	968
1,577	19178	1129

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=24898&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=24898&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24898&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
17.20415440145477
28.75751581271771
320.8061109061737
421.6002342663222
536.6510201234564
643.7818006528968
754.0394992282497
855.1697106413474
956.3027535675654
1061.7172112218302
1168.4170300448653
1275.0179542339033
1381.8752814083104
1486.1664345672216
1588.3457044389256
1690.0933779855101
1794.638546640384
1898.608332196074
19100.373104614533
20104.678621892390
21110.068572824444
22111.553035372776
23118.439516387373
24121.428539319593
25153.661395965953
26163.015157902912
27185.441419946744
28189.608862107693
29190.35504249452
30191.098354855530
31198.278994155723
32222.992943829071
33226.936491263613
34229.934653655664
35241.852680526349
36265.413187480134
37270.218921631927
38279.873134015257
39282.577280868231
40401.58162712244
41449.644667330783
42462.134926752361
43537.208741112394
44743.11661299062
45755.905159584658
46805.676549061245
47827.060977594431
48937.063339539848
491192.85921242141
501216.63528345156
511573.50571062893
521773.79679191880
532308.31009356899
542929.56777876145
554103.92258652658
565717.74468143114
576586.50171807535
5811217.4750954007
5928917.0981165906
60134628.812085719

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 7.20415440145477 \tabularnewline
2 & 8.75751581271771 \tabularnewline
3 & 20.8061109061737 \tabularnewline
4 & 21.6002342663222 \tabularnewline
5 & 36.6510201234564 \tabularnewline
6 & 43.7818006528968 \tabularnewline
7 & 54.0394992282497 \tabularnewline
8 & 55.1697106413474 \tabularnewline
9 & 56.3027535675654 \tabularnewline
10 & 61.7172112218302 \tabularnewline
11 & 68.4170300448653 \tabularnewline
12 & 75.0179542339033 \tabularnewline
13 & 81.8752814083104 \tabularnewline
14 & 86.1664345672216 \tabularnewline
15 & 88.3457044389256 \tabularnewline
16 & 90.0933779855101 \tabularnewline
17 & 94.638546640384 \tabularnewline
18 & 98.608332196074 \tabularnewline
19 & 100.373104614533 \tabularnewline
20 & 104.678621892390 \tabularnewline
21 & 110.068572824444 \tabularnewline
22 & 111.553035372776 \tabularnewline
23 & 118.439516387373 \tabularnewline
24 & 121.428539319593 \tabularnewline
25 & 153.661395965953 \tabularnewline
26 & 163.015157902912 \tabularnewline
27 & 185.441419946744 \tabularnewline
28 & 189.608862107693 \tabularnewline
29 & 190.35504249452 \tabularnewline
30 & 191.098354855530 \tabularnewline
31 & 198.278994155723 \tabularnewline
32 & 222.992943829071 \tabularnewline
33 & 226.936491263613 \tabularnewline
34 & 229.934653655664 \tabularnewline
35 & 241.852680526349 \tabularnewline
36 & 265.413187480134 \tabularnewline
37 & 270.218921631927 \tabularnewline
38 & 279.873134015257 \tabularnewline
39 & 282.577280868231 \tabularnewline
40 & 401.58162712244 \tabularnewline
41 & 449.644667330783 \tabularnewline
42 & 462.134926752361 \tabularnewline
43 & 537.208741112394 \tabularnewline
44 & 743.11661299062 \tabularnewline
45 & 755.905159584658 \tabularnewline
46 & 805.676549061245 \tabularnewline
47 & 827.060977594431 \tabularnewline
48 & 937.063339539848 \tabularnewline
49 & 1192.85921242141 \tabularnewline
50 & 1216.63528345156 \tabularnewline
51 & 1573.50571062893 \tabularnewline
52 & 1773.79679191880 \tabularnewline
53 & 2308.31009356899 \tabularnewline
54 & 2929.56777876145 \tabularnewline
55 & 4103.92258652658 \tabularnewline
56 & 5717.74468143114 \tabularnewline
57 & 6586.50171807535 \tabularnewline
58 & 11217.4750954007 \tabularnewline
59 & 28917.0981165906 \tabularnewline
60 & 134628.812085719 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24898&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]7.20415440145477[/C][/ROW]
[ROW][C]2[/C][C]8.75751581271771[/C][/ROW]
[ROW][C]3[/C][C]20.8061109061737[/C][/ROW]
[ROW][C]4[/C][C]21.6002342663222[/C][/ROW]
[ROW][C]5[/C][C]36.6510201234564[/C][/ROW]
[ROW][C]6[/C][C]43.7818006528968[/C][/ROW]
[ROW][C]7[/C][C]54.0394992282497[/C][/ROW]
[ROW][C]8[/C][C]55.1697106413474[/C][/ROW]
[ROW][C]9[/C][C]56.3027535675654[/C][/ROW]
[ROW][C]10[/C][C]61.7172112218302[/C][/ROW]
[ROW][C]11[/C][C]68.4170300448653[/C][/ROW]
[ROW][C]12[/C][C]75.0179542339033[/C][/ROW]
[ROW][C]13[/C][C]81.8752814083104[/C][/ROW]
[ROW][C]14[/C][C]86.1664345672216[/C][/ROW]
[ROW][C]15[/C][C]88.3457044389256[/C][/ROW]
[ROW][C]16[/C][C]90.0933779855101[/C][/ROW]
[ROW][C]17[/C][C]94.638546640384[/C][/ROW]
[ROW][C]18[/C][C]98.608332196074[/C][/ROW]
[ROW][C]19[/C][C]100.373104614533[/C][/ROW]
[ROW][C]20[/C][C]104.678621892390[/C][/ROW]
[ROW][C]21[/C][C]110.068572824444[/C][/ROW]
[ROW][C]22[/C][C]111.553035372776[/C][/ROW]
[ROW][C]23[/C][C]118.439516387373[/C][/ROW]
[ROW][C]24[/C][C]121.428539319593[/C][/ROW]
[ROW][C]25[/C][C]153.661395965953[/C][/ROW]
[ROW][C]26[/C][C]163.015157902912[/C][/ROW]
[ROW][C]27[/C][C]185.441419946744[/C][/ROW]
[ROW][C]28[/C][C]189.608862107693[/C][/ROW]
[ROW][C]29[/C][C]190.35504249452[/C][/ROW]
[ROW][C]30[/C][C]191.098354855530[/C][/ROW]
[ROW][C]31[/C][C]198.278994155723[/C][/ROW]
[ROW][C]32[/C][C]222.992943829071[/C][/ROW]
[ROW][C]33[/C][C]226.936491263613[/C][/ROW]
[ROW][C]34[/C][C]229.934653655664[/C][/ROW]
[ROW][C]35[/C][C]241.852680526349[/C][/ROW]
[ROW][C]36[/C][C]265.413187480134[/C][/ROW]
[ROW][C]37[/C][C]270.218921631927[/C][/ROW]
[ROW][C]38[/C][C]279.873134015257[/C][/ROW]
[ROW][C]39[/C][C]282.577280868231[/C][/ROW]
[ROW][C]40[/C][C]401.58162712244[/C][/ROW]
[ROW][C]41[/C][C]449.644667330783[/C][/ROW]
[ROW][C]42[/C][C]462.134926752361[/C][/ROW]
[ROW][C]43[/C][C]537.208741112394[/C][/ROW]
[ROW][C]44[/C][C]743.11661299062[/C][/ROW]
[ROW][C]45[/C][C]755.905159584658[/C][/ROW]
[ROW][C]46[/C][C]805.676549061245[/C][/ROW]
[ROW][C]47[/C][C]827.060977594431[/C][/ROW]
[ROW][C]48[/C][C]937.063339539848[/C][/ROW]
[ROW][C]49[/C][C]1192.85921242141[/C][/ROW]
[ROW][C]50[/C][C]1216.63528345156[/C][/ROW]
[ROW][C]51[/C][C]1573.50571062893[/C][/ROW]
[ROW][C]52[/C][C]1773.79679191880[/C][/ROW]
[ROW][C]53[/C][C]2308.31009356899[/C][/ROW]
[ROW][C]54[/C][C]2929.56777876145[/C][/ROW]
[ROW][C]55[/C][C]4103.92258652658[/C][/ROW]
[ROW][C]56[/C][C]5717.74468143114[/C][/ROW]
[ROW][C]57[/C][C]6586.50171807535[/C][/ROW]
[ROW][C]58[/C][C]11217.4750954007[/C][/ROW]
[ROW][C]59[/C][C]28917.0981165906[/C][/ROW]
[ROW][C]60[/C][C]134628.812085719[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24898&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24898&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
17.20415440145477
28.75751581271771
320.8061109061737
421.6002342663222
536.6510201234564
643.7818006528968
754.0394992282497
855.1697106413474
956.3027535675654
1061.7172112218302
1168.4170300448653
1275.0179542339033
1381.8752814083104
1486.1664345672216
1588.3457044389256
1690.0933779855101
1794.638546640384
1898.608332196074
19100.373104614533
20104.678621892390
21110.068572824444
22111.553035372776
23118.439516387373
24121.428539319593
25153.661395965953
26163.015157902912
27185.441419946744
28189.608862107693
29190.35504249452
30191.098354855530
31198.278994155723
32222.992943829071
33226.936491263613
34229.934653655664
35241.852680526349
36265.413187480134
37270.218921631927
38279.873134015257
39282.577280868231
40401.58162712244
41449.644667330783
42462.134926752361
43537.208741112394
44743.11661299062
45755.905159584658
46805.676549061245
47827.060977594431
48937.063339539848
491192.85921242141
501216.63528345156
511573.50571062893
521773.79679191880
532308.31009356899
542929.56777876145
554103.92258652658
565717.74468143114
576586.50171807535
5811217.4750954007
5928917.0981165906
60134628.812085719


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')
}