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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationThu, 13 Nov 2008 13:04:22 -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/13/t1226606802t58f3w1g1eazj2l.htm/, Retrieved Mon, 20 May 2024 09:45:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24813, Retrieved Mon, 20 May 2024 09:45:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Partial Correlation] [Vincent Dolahain ...] [2008-11-13 15:59:08] [17bef6922a2795858ae28bf8ba596537]
F RMPD    [Hierarchical Clustering] [Vincent Dolhain T...] [2008-11-13 20:04:22] [dcb9dbe132bac62365bf3d43fe342148] [Current]
Feedback Forum
2008-11-20 15:57:48 [Marie-Lien Loos] [reply] 
Methode is juist.
Het nut van de dendogram is dat je kan zien welke gegevens er in 1 groep zitten. Hier kan men uit afleiden welke observaties samenhoren en kunne we deze anders behandelen. Het dendogram wordt enkel exploratief gebruikt.
2008-11-24 20:22:05 [Marlies Polfliet] [reply] 
De student heeft de juiste berekeningswijze gehanteerd, maar heeft geen conclusie weergegeven. Een dendogram verdeelt de gelijkaardige gebeurtenissen en splitst ze in takken die gelijkaardige situaties beschrijven m.a.w. alle periodes onder één tak zijn gelijkaardig. (= Een dendogram is een grafische voorstelling van de manier waarop gebeurtenissen/periodes aan elkaar gerelateerd kunnen worden op basis van de berekende gelijkenissen en verschillen.)
2008-11-24 21:14:03 [Erik Geysen] [reply] 
De student heeft hier de dendrogram gebruikt. Dit is ook juist. Het voordeel van de dendrogram is dat men een tijdsreeks kan opsplitsen in verschillende groepen. Zo zien we welke gegevens in een eerste deel zitten en de andere gegevens in een tweede deel. Het gevolg is dat we kunnen zien welke gegevens anders behandeld moeten worden.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.9059
0.8883
0.8924
0.8833
0.87
0.8758
0.8858
0.917
0.9554
0.9922
0.9778
0.9808
0.9811
1.0014
1.0183
1.0622
1.0773
1.0807
1.0848
1.1582
1.1663
1.1372
1.1139
1.1222
1.1692
1.1702
1.2286
1.2613
1.2646
1.2262
1.1985
1.2007
1.2138
1.2266
1.2176
1.2218
1.249
1.2991
1.3408
1.3119
1.3014
1.3201
1.2938
1.2694
1.2165
1.2037
1.2292
1.2256
1.2015
1.1786
1.1856
1.2103
1.1938
1.202
1.2271
1.277
1.265
1.2684
1.2811
1.2727
1.2611
1.2881
1.3213
1.2999
1.3074
1.3242
1.3516
1.3511
1.3419
1.3716
1.3622
1.3896
1.4227
1.4684

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=24813&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=24813&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24813&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
10.000199999999999978
20.000299999999999967
30.000399999999999956
40.000399999999999956
50.000499999999999945
60.000499999999999945
70.000600000000000156
80.000800000000000134
90.000800000000000208
100.00099999999999989
110.00100000000000011
120.00110000000000010
130.00110000000000010
140.00119999999999987
150.00123333333333320
160.0012499999999999
170.00226666666666649
180.00249999999999995
190.00301666666666667
200.00340000000000007
210.00350000000000006
220.00409999999999999
230.00409999999999999
240.00416666666666673
250.00420000000000013
260.00426666666666679
270.00450000000000017
280.00461000000000023
290.00473333333333318
300.00551666666666654
310.00570000000000004
320.00580000000000003
330.00596666666666668
340.00660000000000001
350.00689999999999968
360.0069999999999999
370.00823333333333330
380.0083000000000002
390.0092000000000001
400.00939999999999985
410.0108733333333333
420.0109066666666667
430.0111
440.0142500000000001
450.0165666666666665
460.0173933333333331
470.0191999999999998
480.0208999999999999
490.0227666666666666
500.0244333333333333
510.0255999999999999
520.0255999999999999
530.0271333333333333
540.0299666666666666
550.0318500000000003
560.0356500
570.0402
580.0455933333333334
590.0456999999999999
600.0655583333333335
610.0664642857142858
620.066609523809524
630.0723200
640.131686274509804
650.132190476190476
660.208046031746032
670.27870358056266
680.283660000000000
690.588747380952381
700.709515938697318
710.855833002070393
722.42351359049289
735.5997379783173

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 0.000199999999999978 \tabularnewline
2 & 0.000299999999999967 \tabularnewline
3 & 0.000399999999999956 \tabularnewline
4 & 0.000399999999999956 \tabularnewline
5 & 0.000499999999999945 \tabularnewline
6 & 0.000499999999999945 \tabularnewline
7 & 0.000600000000000156 \tabularnewline
8 & 0.000800000000000134 \tabularnewline
9 & 0.000800000000000208 \tabularnewline
10 & 0.00099999999999989 \tabularnewline
11 & 0.00100000000000011 \tabularnewline
12 & 0.00110000000000010 \tabularnewline
13 & 0.00110000000000010 \tabularnewline
14 & 0.00119999999999987 \tabularnewline
15 & 0.00123333333333320 \tabularnewline
16 & 0.0012499999999999 \tabularnewline
17 & 0.00226666666666649 \tabularnewline
18 & 0.00249999999999995 \tabularnewline
19 & 0.00301666666666667 \tabularnewline
20 & 0.00340000000000007 \tabularnewline
21 & 0.00350000000000006 \tabularnewline
22 & 0.00409999999999999 \tabularnewline
23 & 0.00409999999999999 \tabularnewline
24 & 0.00416666666666673 \tabularnewline
25 & 0.00420000000000013 \tabularnewline
26 & 0.00426666666666679 \tabularnewline
27 & 0.00450000000000017 \tabularnewline
28 & 0.00461000000000023 \tabularnewline
29 & 0.00473333333333318 \tabularnewline
30 & 0.00551666666666654 \tabularnewline
31 & 0.00570000000000004 \tabularnewline
32 & 0.00580000000000003 \tabularnewline
33 & 0.00596666666666668 \tabularnewline
34 & 0.00660000000000001 \tabularnewline
35 & 0.00689999999999968 \tabularnewline
36 & 0.0069999999999999 \tabularnewline
37 & 0.00823333333333330 \tabularnewline
38 & 0.0083000000000002 \tabularnewline
39 & 0.0092000000000001 \tabularnewline
40 & 0.00939999999999985 \tabularnewline
41 & 0.0108733333333333 \tabularnewline
42 & 0.0109066666666667 \tabularnewline
43 & 0.0111 \tabularnewline
44 & 0.0142500000000001 \tabularnewline
45 & 0.0165666666666665 \tabularnewline
46 & 0.0173933333333331 \tabularnewline
47 & 0.0191999999999998 \tabularnewline
48 & 0.0208999999999999 \tabularnewline
49 & 0.0227666666666666 \tabularnewline
50 & 0.0244333333333333 \tabularnewline
51 & 0.0255999999999999 \tabularnewline
52 & 0.0255999999999999 \tabularnewline
53 & 0.0271333333333333 \tabularnewline
54 & 0.0299666666666666 \tabularnewline
55 & 0.0318500000000003 \tabularnewline
56 & 0.0356500 \tabularnewline
57 & 0.0402 \tabularnewline
58 & 0.0455933333333334 \tabularnewline
59 & 0.0456999999999999 \tabularnewline
60 & 0.0655583333333335 \tabularnewline
61 & 0.0664642857142858 \tabularnewline
62 & 0.066609523809524 \tabularnewline
63 & 0.0723200 \tabularnewline
64 & 0.131686274509804 \tabularnewline
65 & 0.132190476190476 \tabularnewline
66 & 0.208046031746032 \tabularnewline
67 & 0.27870358056266 \tabularnewline
68 & 0.283660000000000 \tabularnewline
69 & 0.588747380952381 \tabularnewline
70 & 0.709515938697318 \tabularnewline
71 & 0.855833002070393 \tabularnewline
72 & 2.42351359049289 \tabularnewline
73 & 5.5997379783173 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24813&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]0.000199999999999978[/C][/ROW]
[ROW][C]2[/C][C]0.000299999999999967[/C][/ROW]
[ROW][C]3[/C][C]0.000399999999999956[/C][/ROW]
[ROW][C]4[/C][C]0.000399999999999956[/C][/ROW]
[ROW][C]5[/C][C]0.000499999999999945[/C][/ROW]
[ROW][C]6[/C][C]0.000499999999999945[/C][/ROW]
[ROW][C]7[/C][C]0.000600000000000156[/C][/ROW]
[ROW][C]8[/C][C]0.000800000000000134[/C][/ROW]
[ROW][C]9[/C][C]0.000800000000000208[/C][/ROW]
[ROW][C]10[/C][C]0.00099999999999989[/C][/ROW]
[ROW][C]11[/C][C]0.00100000000000011[/C][/ROW]
[ROW][C]12[/C][C]0.00110000000000010[/C][/ROW]
[ROW][C]13[/C][C]0.00110000000000010[/C][/ROW]
[ROW][C]14[/C][C]0.00119999999999987[/C][/ROW]
[ROW][C]15[/C][C]0.00123333333333320[/C][/ROW]
[ROW][C]16[/C][C]0.0012499999999999[/C][/ROW]
[ROW][C]17[/C][C]0.00226666666666649[/C][/ROW]
[ROW][C]18[/C][C]0.00249999999999995[/C][/ROW]
[ROW][C]19[/C][C]0.00301666666666667[/C][/ROW]
[ROW][C]20[/C][C]0.00340000000000007[/C][/ROW]
[ROW][C]21[/C][C]0.00350000000000006[/C][/ROW]
[ROW][C]22[/C][C]0.00409999999999999[/C][/ROW]
[ROW][C]23[/C][C]0.00409999999999999[/C][/ROW]
[ROW][C]24[/C][C]0.00416666666666673[/C][/ROW]
[ROW][C]25[/C][C]0.00420000000000013[/C][/ROW]
[ROW][C]26[/C][C]0.00426666666666679[/C][/ROW]
[ROW][C]27[/C][C]0.00450000000000017[/C][/ROW]
[ROW][C]28[/C][C]0.00461000000000023[/C][/ROW]
[ROW][C]29[/C][C]0.00473333333333318[/C][/ROW]
[ROW][C]30[/C][C]0.00551666666666654[/C][/ROW]
[ROW][C]31[/C][C]0.00570000000000004[/C][/ROW]
[ROW][C]32[/C][C]0.00580000000000003[/C][/ROW]
[ROW][C]33[/C][C]0.00596666666666668[/C][/ROW]
[ROW][C]34[/C][C]0.00660000000000001[/C][/ROW]
[ROW][C]35[/C][C]0.00689999999999968[/C][/ROW]
[ROW][C]36[/C][C]0.0069999999999999[/C][/ROW]
[ROW][C]37[/C][C]0.00823333333333330[/C][/ROW]
[ROW][C]38[/C][C]0.0083000000000002[/C][/ROW]
[ROW][C]39[/C][C]0.0092000000000001[/C][/ROW]
[ROW][C]40[/C][C]0.00939999999999985[/C][/ROW]
[ROW][C]41[/C][C]0.0108733333333333[/C][/ROW]
[ROW][C]42[/C][C]0.0109066666666667[/C][/ROW]
[ROW][C]43[/C][C]0.0111[/C][/ROW]
[ROW][C]44[/C][C]0.0142500000000001[/C][/ROW]
[ROW][C]45[/C][C]0.0165666666666665[/C][/ROW]
[ROW][C]46[/C][C]0.0173933333333331[/C][/ROW]
[ROW][C]47[/C][C]0.0191999999999998[/C][/ROW]
[ROW][C]48[/C][C]0.0208999999999999[/C][/ROW]
[ROW][C]49[/C][C]0.0227666666666666[/C][/ROW]
[ROW][C]50[/C][C]0.0244333333333333[/C][/ROW]
[ROW][C]51[/C][C]0.0255999999999999[/C][/ROW]
[ROW][C]52[/C][C]0.0255999999999999[/C][/ROW]
[ROW][C]53[/C][C]0.0271333333333333[/C][/ROW]
[ROW][C]54[/C][C]0.0299666666666666[/C][/ROW]
[ROW][C]55[/C][C]0.0318500000000003[/C][/ROW]
[ROW][C]56[/C][C]0.0356500[/C][/ROW]
[ROW][C]57[/C][C]0.0402[/C][/ROW]
[ROW][C]58[/C][C]0.0455933333333334[/C][/ROW]
[ROW][C]59[/C][C]0.0456999999999999[/C][/ROW]
[ROW][C]60[/C][C]0.0655583333333335[/C][/ROW]
[ROW][C]61[/C][C]0.0664642857142858[/C][/ROW]
[ROW][C]62[/C][C]0.066609523809524[/C][/ROW]
[ROW][C]63[/C][C]0.0723200[/C][/ROW]
[ROW][C]64[/C][C]0.131686274509804[/C][/ROW]
[ROW][C]65[/C][C]0.132190476190476[/C][/ROW]
[ROW][C]66[/C][C]0.208046031746032[/C][/ROW]
[ROW][C]67[/C][C]0.27870358056266[/C][/ROW]
[ROW][C]68[/C][C]0.283660000000000[/C][/ROW]
[ROW][C]69[/C][C]0.588747380952381[/C][/ROW]
[ROW][C]70[/C][C]0.709515938697318[/C][/ROW]
[ROW][C]71[/C][C]0.855833002070393[/C][/ROW]
[ROW][C]72[/C][C]2.42351359049289[/C][/ROW]
[ROW][C]73[/C][C]5.5997379783173[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24813&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24813&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
10.000199999999999978
20.000299999999999967
30.000399999999999956
40.000399999999999956
50.000499999999999945
60.000499999999999945
70.000600000000000156
80.000800000000000134
90.000800000000000208
100.00099999999999989
110.00100000000000011
120.00110000000000010
130.00110000000000010
140.00119999999999987
150.00123333333333320
160.0012499999999999
170.00226666666666649
180.00249999999999995
190.00301666666666667
200.00340000000000007
210.00350000000000006
220.00409999999999999
230.00409999999999999
240.00416666666666673
250.00420000000000013
260.00426666666666679
270.00450000000000017
280.00461000000000023
290.00473333333333318
300.00551666666666654
310.00570000000000004
320.00580000000000003
330.00596666666666668
340.00660000000000001
350.00689999999999968
360.0069999999999999
370.00823333333333330
380.0083000000000002
390.0092000000000001
400.00939999999999985
410.0108733333333333
420.0109066666666667
430.0111
440.0142500000000001
450.0165666666666665
460.0173933333333331
470.0191999999999998
480.0208999999999999
490.0227666666666666
500.0244333333333333
510.0255999999999999
520.0255999999999999
530.0271333333333333
540.0299666666666666
550.0318500000000003
560.0356500
570.0402
580.0455933333333334
590.0456999999999999
600.0655583333333335
610.0664642857142858
620.066609523809524
630.0723200
640.131686274509804
650.132190476190476
660.208046031746032
670.27870358056266
680.283660000000000
690.588747380952381
700.709515938697318
710.855833002070393
722.42351359049289
735.5997379783173


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')
}