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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 14:08:42 -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/t1226610561qmzsvszg42io1do.htm/, Retrieved Sun, 19 May 2024 10:50:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24831, Retrieved Sun, 19 May 2024 10:50:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordskleuter
Estimated Impact130

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] [] [2008-11-13 21:08:42] [b5c0979bf79a38ace87e0d3abace1ca1] [Current]
Feedback Forum
2008-11-20 12:32:00 [Steven Vanhooreweghe] [reply] 
Een dendogram dient om weer te geven waar de clusters zich bevinden.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7,5	9,4	63,3
7,6	9,5	102,9
7,9	9,1	107,6
7,9	9	93
8,1	9,3	84,1
8,2	9,9	89,7
8	9,8	90,1
7,5	9,4	103,4
6,8	8,3	95,6
6,5	8	90,4
6,6	8,5	104,1
7,6	10,4	82,8
8	11,1	69
8	10,9	105,1
7,7	9,9	104,3
7,5	9,2	95,4
7,6	9,2	93
7,7	9,5	89,3
7,9	9,6	85,2
7,8	9,5	96,4
7,5	9,1	93,1
7,5	8,9	83,3
7,1	9	98,4
7,5	10,1	76,9
7,5	10,3	66,3
7,6	10,2	98,6
7,7	9,6	92,3
7,7	9,2	96,1
7,9	9,3	84,4
8,1	9,4	85,8
8,2	9,4	94,6
8,2	9,2	101,5
8,1	9	86
7,9	9	91,1
7,3	9	101,8
6,9	9,8	79,4
6,6	10	67,3
6,7	9,9	98,1
6,9	9,3	104,7
7	9	102,9
7,1	9	82,8
7,2	9,1	94,5
7,1	9,1	93,1
6,9	9,1	103,6
7	9,2	89,9
6,8	8,8	92,5
6,4	8,3	103,5
6,7	8,4	86,9
6,7	8,1	69,5
6,4	7,8	97,1
6,3	7,9	109,8
6,2	7,9	96,6
6,5	8	75,8
6,8	7,9	127,5
6,8	7,5	93,4
6,5	7,2	87,7
6,3	6,9	94
5,9	6,6	84
5,9	6,7	90,1
6,4	7,3	81,5
6,4	7,5	58,6

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24831&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24831&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24831&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'George Udny Yule' @ 72.249.76.132






Summary of Dendrogram
LabelHeight
10.173205080756884
20.360555127546408
30.435889894354076
40.447213595499960
50.458257569495576
60.46547777058659
70.519615242270663
80.547722557505166
90.648074069840786
100.663324958071074
110.706338828531261
120.714142842854274
130.95393920141695
140.95426211506202
150.969535971483264
160.9730147086931
170.984885780179607
181.02956301409870
191.06368927406622
201.07703296142690
211.10233642006725
221.22065556157337
231.24859577748240
241.33523035260091
251.37840487520902
261.39283882771841
271.45602197785610
281.72664810991415
291.78284849552241
301.83124519439130
311.83946728216202
322.42918214355644
332.50242422280418
342.57293606605372
352.60579752548171
362.64386081328046
372.91072299810364
382.9732137494637
393.08838281108583
403.56447831420896
413.97381333666521
423.99503170527562
434.22990448448517
445.04508738531503
455.0775080448744
465.15462525144936
475.18748493973717
485.32174424817027
495.989854072773
508.09025307743049
5110.0699987504817
5213.2348711488524
5313.3924241639698
5414.1798064761527
5524.2991467458092
5636.2810927133402
5740.8180339789969
58113.376682802009
59141.548020922459
60309.25619016811

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 0.173205080756884 \tabularnewline
2 & 0.360555127546408 \tabularnewline
3 & 0.435889894354076 \tabularnewline
4 & 0.447213595499960 \tabularnewline
5 & 0.458257569495576 \tabularnewline
6 & 0.46547777058659 \tabularnewline
7 & 0.519615242270663 \tabularnewline
8 & 0.547722557505166 \tabularnewline
9 & 0.648074069840786 \tabularnewline
10 & 0.663324958071074 \tabularnewline
11 & 0.706338828531261 \tabularnewline
12 & 0.714142842854274 \tabularnewline
13 & 0.95393920141695 \tabularnewline
14 & 0.95426211506202 \tabularnewline
15 & 0.969535971483264 \tabularnewline
16 & 0.9730147086931 \tabularnewline
17 & 0.984885780179607 \tabularnewline
18 & 1.02956301409870 \tabularnewline
19 & 1.06368927406622 \tabularnewline
20 & 1.07703296142690 \tabularnewline
21 & 1.10233642006725 \tabularnewline
22 & 1.22065556157337 \tabularnewline
23 & 1.24859577748240 \tabularnewline
24 & 1.33523035260091 \tabularnewline
25 & 1.37840487520902 \tabularnewline
26 & 1.39283882771841 \tabularnewline
27 & 1.45602197785610 \tabularnewline
28 & 1.72664810991415 \tabularnewline
29 & 1.78284849552241 \tabularnewline
30 & 1.83124519439130 \tabularnewline
31 & 1.83946728216202 \tabularnewline
32 & 2.42918214355644 \tabularnewline
33 & 2.50242422280418 \tabularnewline
34 & 2.57293606605372 \tabularnewline
35 & 2.60579752548171 \tabularnewline
36 & 2.64386081328046 \tabularnewline
37 & 2.91072299810364 \tabularnewline
38 & 2.9732137494637 \tabularnewline
39 & 3.08838281108583 \tabularnewline
40 & 3.56447831420896 \tabularnewline
41 & 3.97381333666521 \tabularnewline
42 & 3.99503170527562 \tabularnewline
43 & 4.22990448448517 \tabularnewline
44 & 5.04508738531503 \tabularnewline
45 & 5.0775080448744 \tabularnewline
46 & 5.15462525144936 \tabularnewline
47 & 5.18748493973717 \tabularnewline
48 & 5.32174424817027 \tabularnewline
49 & 5.989854072773 \tabularnewline
50 & 8.09025307743049 \tabularnewline
51 & 10.0699987504817 \tabularnewline
52 & 13.2348711488524 \tabularnewline
53 & 13.3924241639698 \tabularnewline
54 & 14.1798064761527 \tabularnewline
55 & 24.2991467458092 \tabularnewline
56 & 36.2810927133402 \tabularnewline
57 & 40.8180339789969 \tabularnewline
58 & 113.376682802009 \tabularnewline
59 & 141.548020922459 \tabularnewline
60 & 309.25619016811 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24831&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]0.173205080756884[/C][/ROW]
[ROW][C]2[/C][C]0.360555127546408[/C][/ROW]
[ROW][C]3[/C][C]0.435889894354076[/C][/ROW]
[ROW][C]4[/C][C]0.447213595499960[/C][/ROW]
[ROW][C]5[/C][C]0.458257569495576[/C][/ROW]
[ROW][C]6[/C][C]0.46547777058659[/C][/ROW]
[ROW][C]7[/C][C]0.519615242270663[/C][/ROW]
[ROW][C]8[/C][C]0.547722557505166[/C][/ROW]
[ROW][C]9[/C][C]0.648074069840786[/C][/ROW]
[ROW][C]10[/C][C]0.663324958071074[/C][/ROW]
[ROW][C]11[/C][C]0.706338828531261[/C][/ROW]
[ROW][C]12[/C][C]0.714142842854274[/C][/ROW]
[ROW][C]13[/C][C]0.95393920141695[/C][/ROW]
[ROW][C]14[/C][C]0.95426211506202[/C][/ROW]
[ROW][C]15[/C][C]0.969535971483264[/C][/ROW]
[ROW][C]16[/C][C]0.9730147086931[/C][/ROW]
[ROW][C]17[/C][C]0.984885780179607[/C][/ROW]
[ROW][C]18[/C][C]1.02956301409870[/C][/ROW]
[ROW][C]19[/C][C]1.06368927406622[/C][/ROW]
[ROW][C]20[/C][C]1.07703296142690[/C][/ROW]
[ROW][C]21[/C][C]1.10233642006725[/C][/ROW]
[ROW][C]22[/C][C]1.22065556157337[/C][/ROW]
[ROW][C]23[/C][C]1.24859577748240[/C][/ROW]
[ROW][C]24[/C][C]1.33523035260091[/C][/ROW]
[ROW][C]25[/C][C]1.37840487520902[/C][/ROW]
[ROW][C]26[/C][C]1.39283882771841[/C][/ROW]
[ROW][C]27[/C][C]1.45602197785610[/C][/ROW]
[ROW][C]28[/C][C]1.72664810991415[/C][/ROW]
[ROW][C]29[/C][C]1.78284849552241[/C][/ROW]
[ROW][C]30[/C][C]1.83124519439130[/C][/ROW]
[ROW][C]31[/C][C]1.83946728216202[/C][/ROW]
[ROW][C]32[/C][C]2.42918214355644[/C][/ROW]
[ROW][C]33[/C][C]2.50242422280418[/C][/ROW]
[ROW][C]34[/C][C]2.57293606605372[/C][/ROW]
[ROW][C]35[/C][C]2.60579752548171[/C][/ROW]
[ROW][C]36[/C][C]2.64386081328046[/C][/ROW]
[ROW][C]37[/C][C]2.91072299810364[/C][/ROW]
[ROW][C]38[/C][C]2.9732137494637[/C][/ROW]
[ROW][C]39[/C][C]3.08838281108583[/C][/ROW]
[ROW][C]40[/C][C]3.56447831420896[/C][/ROW]
[ROW][C]41[/C][C]3.97381333666521[/C][/ROW]
[ROW][C]42[/C][C]3.99503170527562[/C][/ROW]
[ROW][C]43[/C][C]4.22990448448517[/C][/ROW]
[ROW][C]44[/C][C]5.04508738531503[/C][/ROW]
[ROW][C]45[/C][C]5.0775080448744[/C][/ROW]
[ROW][C]46[/C][C]5.15462525144936[/C][/ROW]
[ROW][C]47[/C][C]5.18748493973717[/C][/ROW]
[ROW][C]48[/C][C]5.32174424817027[/C][/ROW]
[ROW][C]49[/C][C]5.989854072773[/C][/ROW]
[ROW][C]50[/C][C]8.09025307743049[/C][/ROW]
[ROW][C]51[/C][C]10.0699987504817[/C][/ROW]
[ROW][C]52[/C][C]13.2348711488524[/C][/ROW]
[ROW][C]53[/C][C]13.3924241639698[/C][/ROW]
[ROW][C]54[/C][C]14.1798064761527[/C][/ROW]
[ROW][C]55[/C][C]24.2991467458092[/C][/ROW]
[ROW][C]56[/C][C]36.2810927133402[/C][/ROW]
[ROW][C]57[/C][C]40.8180339789969[/C][/ROW]
[ROW][C]58[/C][C]113.376682802009[/C][/ROW]
[ROW][C]59[/C][C]141.548020922459[/C][/ROW]
[ROW][C]60[/C][C]309.25619016811[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24831&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24831&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
10.173205080756884
20.360555127546408
30.435889894354076
40.447213595499960
50.458257569495576
60.46547777058659
70.519615242270663
80.547722557505166
90.648074069840786
100.663324958071074
110.706338828531261
120.714142842854274
130.95393920141695
140.95426211506202
150.969535971483264
160.9730147086931
170.984885780179607
181.02956301409870
191.06368927406622
201.07703296142690
211.10233642006725
221.22065556157337
231.24859577748240
241.33523035260091
251.37840487520902
261.39283882771841
271.45602197785610
281.72664810991415
291.78284849552241
301.83124519439130
311.83946728216202
322.42918214355644
332.50242422280418
342.57293606605372
352.60579752548171
362.64386081328046
372.91072299810364
382.9732137494637
393.08838281108583
403.56447831420896
413.97381333666521
423.99503170527562
434.22990448448517
445.04508738531503
455.0775080448744
465.15462525144936
475.18748493973717
485.32174424817027
495.989854072773
508.09025307743049
5110.0699987504817
5213.2348711488524
5313.3924241639698
5414.1798064761527
5524.2991467458092
5636.2810927133402
5740.8180339789969
58113.376682802009
59141.548020922459
60309.25619016811


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')
}