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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 computationSat, 08 Nov 2008 09:15:32 -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/08/t122616100258wnu8zkoyblz2j.htm/, Retrieved Mon, 20 May 2024 09:47:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22624, Retrieved Mon, 20 May 2024 09:47:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154

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] [EDA Hyp. Testing Q2] [2008-11-08 16:15:32] [0da3c04827d8ef68db874351a2e09488] [Current]
Feedback Forum
2008-11-21 16:08:58 [Nick Wuyts] [reply] 
De dendogram grafiek toont ons een soort van boomstructuur. De waarden van de 4 reeksen worden verdeeld in clusters. De grafiek geeft weer waar de clusters/subsets zich bevinden.
De gelijkaardige waarden worden samengebracht (clusteren), je kan blijven splitsen tot je uiteindelijk 1 observatie bekomt.
Deze techniek wordt puur exploratief gebruikt, en dus niet bij tijdreeksen zoals hier het geval is. Wel wordt dit gebruikt bij bv een assortiment producten (marketing), om te weten welke in dezelfde groep horen en je dus samen kunt verkopen.
2008-11-24 19:15:10 [Bart Haemels] [reply] 
Op een Dendrogram worden gelijkaardige observaties gegroepeerd. Ze worden hiërarchisch in groepjes geordend. Meestal wordt deze techniek gebruikt voor niet tijdreeksen, wel voor marketingdoeleinden.

Deze methode kon je hier niet gebruiken.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8,4	1,7	2	94,7
8,4	1,4	2	101,8
8,4	1,8	2	102,5
8,6	1,7	2	105,3
8,9	1,4	2	110,3
8,8	1,2	2	109,8
8,3	1	2	117,3
7,5	1,7	2	118,8
7,2	2,4	2	131,3
7,5	2	2	125,9
8,8	2,1	2	133,1
9,3	2	2	147
9,3	1,8	2	145,8
8,7	2,7	2	164,4
8,2	2,3	2	149,8
8,3	1,9	2	137,7
8,5	2	2	151,7
8,6	2,3	2	156,8
8,6	2,8	2	180
8,2	2,4	2	180,4
8,1	2,3	2	170,4
8	2,7	2	191,6
8,6	2,7	2	199,5
8,7	2,9	2	218,2
8,8	3	2	217,5
8,5	2,2	2	205
8,4	2,3	2	194
8,5	2,8	2,21	199,3
8,7	2,8	2,25	219,3
8,7	2,8	2,25	211,1
8,6	2,2	2,45	215,2
8,5	2,6	2,5	240,2
8,3	2,8	2,5	242,2
8,1	2,5	2,64	240,7
8,2	2,4	2,75	255,4
8,1	2,3	2,93	253
8,1	1,9	3	218,2
7,9	1,7	3,17	203,7
7,9	2	3,25	205,6
7,9	2,1	3,39	215,6
8	1,7	3,5	188,5
8	1,8	3,5	202,9
7,9	1,8	3,65	214
8	1,8	3,75	230,3
7,7	1,3	3,75	230
7,2	1,3	3,9	241
7,5	1,3	4	259,6
7,3	1,2	4	247,8
7	1,4	4	270,3
7	2,2	4	289,7
7	2,9	4	322,7
7,2	3,1	4	315
7,3	3,5	4	320,2
7,1	3,6	4	329,5
6,8	4,4	4	360,6
6,6	4,1	4	382,2
6,2	5,1	4	435,4
6,2	5,8	4	464
6,8	5,9	4,18	468,8
6,9	5,4	4,25	403
6,8	5,5	4,25	351,6

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22624&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22624&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22624&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Summary of Dendrogram
LabelHeight
10.322645316098026
20.547722557505166
30.655743852430205
40.663023378170031
50.692820323027554
60.714142842854274
70.806225774829858
80.8768694315575
91.21655250605963
101.24241699923979
111.52397506541281
121.71537167984086
131.83847763108502
141.92811512223923
151.93742360399018
161.94679223339316
172.1583023548306
182.41089195112515
192.42693221990231
202.46576560118760
212.58843582110896
222.81785925207929
233.40974740511955
243.94954927384969
254.84173522613537
265.39381676827276
275.39966971615858
286.04317797189525
296.6206747706574
306.76906133926299
317.38168120756765
327.75153045718786
339.07041895394033
349.9212816226314
3510.1723402393434
3611.0847332746534
3711.5426223973721
3811.5654876506488
3911.7920233572216
4012.7391666228826
4118.1822608669291
4219.2735543314084
4320.8442438097428
4422.2511352914746
4529.847033543981
4630.2125764391685
4734.3188345874839
4839.7354327024521
4942.5535458979299
5058.0674344003904
5179.1492227322516
5295.265301410092
5397.0315791005339
54105.177505917589
55154.61446509068
56310.48293474195
57366.318972963334
58402.226402749435
591488.9040631967
602354.57583284781

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 0.322645316098026 \tabularnewline
2 & 0.547722557505166 \tabularnewline
3 & 0.655743852430205 \tabularnewline
4 & 0.663023378170031 \tabularnewline
5 & 0.692820323027554 \tabularnewline
6 & 0.714142842854274 \tabularnewline
7 & 0.806225774829858 \tabularnewline
8 & 0.8768694315575 \tabularnewline
9 & 1.21655250605963 \tabularnewline
10 & 1.24241699923979 \tabularnewline
11 & 1.52397506541281 \tabularnewline
12 & 1.71537167984086 \tabularnewline
13 & 1.83847763108502 \tabularnewline
14 & 1.92811512223923 \tabularnewline
15 & 1.93742360399018 \tabularnewline
16 & 1.94679223339316 \tabularnewline
17 & 2.1583023548306 \tabularnewline
18 & 2.41089195112515 \tabularnewline
19 & 2.42693221990231 \tabularnewline
20 & 2.46576560118760 \tabularnewline
21 & 2.58843582110896 \tabularnewline
22 & 2.81785925207929 \tabularnewline
23 & 3.40974740511955 \tabularnewline
24 & 3.94954927384969 \tabularnewline
25 & 4.84173522613537 \tabularnewline
26 & 5.39381676827276 \tabularnewline
27 & 5.39966971615858 \tabularnewline
28 & 6.04317797189525 \tabularnewline
29 & 6.6206747706574 \tabularnewline
30 & 6.76906133926299 \tabularnewline
31 & 7.38168120756765 \tabularnewline
32 & 7.75153045718786 \tabularnewline
33 & 9.07041895394033 \tabularnewline
34 & 9.9212816226314 \tabularnewline
35 & 10.1723402393434 \tabularnewline
36 & 11.0847332746534 \tabularnewline
37 & 11.5426223973721 \tabularnewline
38 & 11.5654876506488 \tabularnewline
39 & 11.7920233572216 \tabularnewline
40 & 12.7391666228826 \tabularnewline
41 & 18.1822608669291 \tabularnewline
42 & 19.2735543314084 \tabularnewline
43 & 20.8442438097428 \tabularnewline
44 & 22.2511352914746 \tabularnewline
45 & 29.847033543981 \tabularnewline
46 & 30.2125764391685 \tabularnewline
47 & 34.3188345874839 \tabularnewline
48 & 39.7354327024521 \tabularnewline
49 & 42.5535458979299 \tabularnewline
50 & 58.0674344003904 \tabularnewline
51 & 79.1492227322516 \tabularnewline
52 & 95.265301410092 \tabularnewline
53 & 97.0315791005339 \tabularnewline
54 & 105.177505917589 \tabularnewline
55 & 154.61446509068 \tabularnewline
56 & 310.48293474195 \tabularnewline
57 & 366.318972963334 \tabularnewline
58 & 402.226402749435 \tabularnewline
59 & 1488.9040631967 \tabularnewline
60 & 2354.57583284781 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22624&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]0.322645316098026[/C][/ROW]
[ROW][C]2[/C][C]0.547722557505166[/C][/ROW]
[ROW][C]3[/C][C]0.655743852430205[/C][/ROW]
[ROW][C]4[/C][C]0.663023378170031[/C][/ROW]
[ROW][C]5[/C][C]0.692820323027554[/C][/ROW]
[ROW][C]6[/C][C]0.714142842854274[/C][/ROW]
[ROW][C]7[/C][C]0.806225774829858[/C][/ROW]
[ROW][C]8[/C][C]0.8768694315575[/C][/ROW]
[ROW][C]9[/C][C]1.21655250605963[/C][/ROW]
[ROW][C]10[/C][C]1.24241699923979[/C][/ROW]
[ROW][C]11[/C][C]1.52397506541281[/C][/ROW]
[ROW][C]12[/C][C]1.71537167984086[/C][/ROW]
[ROW][C]13[/C][C]1.83847763108502[/C][/ROW]
[ROW][C]14[/C][C]1.92811512223923[/C][/ROW]
[ROW][C]15[/C][C]1.93742360399018[/C][/ROW]
[ROW][C]16[/C][C]1.94679223339316[/C][/ROW]
[ROW][C]17[/C][C]2.1583023548306[/C][/ROW]
[ROW][C]18[/C][C]2.41089195112515[/C][/ROW]
[ROW][C]19[/C][C]2.42693221990231[/C][/ROW]
[ROW][C]20[/C][C]2.46576560118760[/C][/ROW]
[ROW][C]21[/C][C]2.58843582110896[/C][/ROW]
[ROW][C]22[/C][C]2.81785925207929[/C][/ROW]
[ROW][C]23[/C][C]3.40974740511955[/C][/ROW]
[ROW][C]24[/C][C]3.94954927384969[/C][/ROW]
[ROW][C]25[/C][C]4.84173522613537[/C][/ROW]
[ROW][C]26[/C][C]5.39381676827276[/C][/ROW]
[ROW][C]27[/C][C]5.39966971615858[/C][/ROW]
[ROW][C]28[/C][C]6.04317797189525[/C][/ROW]
[ROW][C]29[/C][C]6.6206747706574[/C][/ROW]
[ROW][C]30[/C][C]6.76906133926299[/C][/ROW]
[ROW][C]31[/C][C]7.38168120756765[/C][/ROW]
[ROW][C]32[/C][C]7.75153045718786[/C][/ROW]
[ROW][C]33[/C][C]9.07041895394033[/C][/ROW]
[ROW][C]34[/C][C]9.9212816226314[/C][/ROW]
[ROW][C]35[/C][C]10.1723402393434[/C][/ROW]
[ROW][C]36[/C][C]11.0847332746534[/C][/ROW]
[ROW][C]37[/C][C]11.5426223973721[/C][/ROW]
[ROW][C]38[/C][C]11.5654876506488[/C][/ROW]
[ROW][C]39[/C][C]11.7920233572216[/C][/ROW]
[ROW][C]40[/C][C]12.7391666228826[/C][/ROW]
[ROW][C]41[/C][C]18.1822608669291[/C][/ROW]
[ROW][C]42[/C][C]19.2735543314084[/C][/ROW]
[ROW][C]43[/C][C]20.8442438097428[/C][/ROW]
[ROW][C]44[/C][C]22.2511352914746[/C][/ROW]
[ROW][C]45[/C][C]29.847033543981[/C][/ROW]
[ROW][C]46[/C][C]30.2125764391685[/C][/ROW]
[ROW][C]47[/C][C]34.3188345874839[/C][/ROW]
[ROW][C]48[/C][C]39.7354327024521[/C][/ROW]
[ROW][C]49[/C][C]42.5535458979299[/C][/ROW]
[ROW][C]50[/C][C]58.0674344003904[/C][/ROW]
[ROW][C]51[/C][C]79.1492227322516[/C][/ROW]
[ROW][C]52[/C][C]95.265301410092[/C][/ROW]
[ROW][C]53[/C][C]97.0315791005339[/C][/ROW]
[ROW][C]54[/C][C]105.177505917589[/C][/ROW]
[ROW][C]55[/C][C]154.61446509068[/C][/ROW]
[ROW][C]56[/C][C]310.48293474195[/C][/ROW]
[ROW][C]57[/C][C]366.318972963334[/C][/ROW]
[ROW][C]58[/C][C]402.226402749435[/C][/ROW]
[ROW][C]59[/C][C]1488.9040631967[/C][/ROW]
[ROW][C]60[/C][C]2354.57583284781[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22624&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22624&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
10.322645316098026
20.547722557505166
30.655743852430205
40.663023378170031
50.692820323027554
60.714142842854274
70.806225774829858
80.8768694315575
91.21655250605963
101.24241699923979
111.52397506541281
121.71537167984086
131.83847763108502
141.92811512223923
151.93742360399018
161.94679223339316
172.1583023548306
182.41089195112515
192.42693221990231
202.46576560118760
212.58843582110896
222.81785925207929
233.40974740511955
243.94954927384969
254.84173522613537
265.39381676827276
275.39966971615858
286.04317797189525
296.6206747706574
306.76906133926299
317.38168120756765
327.75153045718786
339.07041895394033
349.9212816226314
3510.1723402393434
3611.0847332746534
3711.5426223973721
3811.5654876506488
3911.7920233572216
4012.7391666228826
4118.1822608669291
4219.2735543314084
4320.8442438097428
4422.2511352914746
4529.847033543981
4630.2125764391685
4734.3188345874839
4839.7354327024521
4942.5535458979299
5058.0674344003904
5179.1492227322516
5295.265301410092
5397.0315791005339
54105.177505917589
55154.61446509068
56310.48293474195
57366.318972963334
58402.226402749435
591488.9040631967
602354.57583284781


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')
}