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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 computationMon, 05 Nov 2007 15:37:50 -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/2007/Nov/05/n6e6bcux5phr0vb1194302131.htm/, Retrieved Sun, 28 Apr 2024 19:08:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=500, Retrieved Sun, 28 Apr 2024 19:08:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsClustering
Estimated Impact196

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Hierarchical Clustering] [WS4Q2] [2007-11-05 22:37:50] [f15e5fe6fe718a2cea2c195ef11f432f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
110,40	109,20	72,50
96,40	88,60	59,40
101,90	94,30	85,70
106,20	98,30	88,20
81,00	86,40	62,80
94,70	80,60	87,00
101,00	104,10	79,20
109,40	108,20	112,00
102,30	93,40	79,20
90,70	71,90	132,10
96,20	94,10	40,10
96,10	94,90	69,00
106,00	96,40	9,40
103,10	91,10	73,80
102,00	84,40	57,40
104,70	86,40	81,10
86,00	88,00	46,60
92,10	75,10	41,40
106,90	109,70	71,20
112,60	103,00	67,90
101,70	82,10	72,00
92,00	68,00	145,50
97,40	96,40	39,70
97,00	94,30	51,90
105,40	90,00	73,70
102,70	88,00	70,90
98,10	76,10	60,80
104,50	82,50	61,00
87,40	81,40	54,50
89,90	66,50	39,10
109,80	97,20	66,60
111,70	94,10	58,50
98,60	80,70	59,80
96,90	70,50	80,90
95,10	87,80	37,30
97,00	89,50	44,60
112,70	99,60	48,70
102,90	84,20	54,00
97,40	75,10	49,50
111,40	92,00	61,60
87,40	80,80	35,00
96,80	73,10	35,70
114,10	99,80	51,30
110,30	90,00	49,00
103,90	83,10	41,50
101,60	72,40	72,50
94,60	78,80	42,10
95,90	87,30	44,10
104,70	91,00	45,10
102,80	80,10	50,30
98,10	73,60	40,90
113,90	86,40	47,20
80,90	74,50	36,90
95,70	71,20	40,90
113,20	92,40	38,30
105,90	81,50	46,30
108,80	85,30	28,40
102,30	69,90	78,40
99,00	84,20	36,80
100,70	90,70	50,70
115,50	100,30	42,80

Tables (Output of Computation)





Summary of compuational 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 compuational 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=500&T=0

[TABLE]
[ROW][C]Summary of compuational 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=500&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=500&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 compuational 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
12.50998007960223
22.55147016443462
32.62488094968135
42.95972971738974
53.39411254969542
63.52278299076171
73.75632799419859
83.76696164036747
94.51995575199581
104.73392015141786
114.9079010563827
125.25071423713004
135.3
145.33104117410474
155.4
165.98080262172226
176.22047838353215
186.38278935889318
196.57038811639008
206.92977413024462
217.64002617796562
228.1182593038984
238.84449713737402
249.14484046179746
259.24932429964481
269.79679727033635
2710.2633740269860
2810.3190669237608
2910.3889364229453
3010.9233182808928
3112.4385046704342
3212.4559042613586
3312.7379027446850
3413.0859465167102
3513.4612099618835
3613.5073998026292
3714.0164189435105
3814.3912885718970
3914.7637011071232
4015.6316076178584
4115.723826795461
4215.8251255223825
4319.1557298969079
4422.1822000712283
4523.6165150580646
4624.7990771325046
4725.0581987388767
4832.7135379049812
4935.9511110358936
5037.9070147502445
5147.515108829537
5258.1162506945276
5362.3543610990595
5466.5046927196352
5567.3167385760507
5696.46840019713
57100.882219742585
58132.371302918782
59201.190158639282
60513.762410088595

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 2.50998007960223 \tabularnewline
2 & 2.55147016443462 \tabularnewline
3 & 2.62488094968135 \tabularnewline
4 & 2.95972971738974 \tabularnewline
5 & 3.39411254969542 \tabularnewline
6 & 3.52278299076171 \tabularnewline
7 & 3.75632799419859 \tabularnewline
8 & 3.76696164036747 \tabularnewline
9 & 4.51995575199581 \tabularnewline
10 & 4.73392015141786 \tabularnewline
11 & 4.9079010563827 \tabularnewline
12 & 5.25071423713004 \tabularnewline
13 & 5.3 \tabularnewline
14 & 5.33104117410474 \tabularnewline
15 & 5.4 \tabularnewline
16 & 5.98080262172226 \tabularnewline
17 & 6.22047838353215 \tabularnewline
18 & 6.38278935889318 \tabularnewline
19 & 6.57038811639008 \tabularnewline
20 & 6.92977413024462 \tabularnewline
21 & 7.64002617796562 \tabularnewline
22 & 8.1182593038984 \tabularnewline
23 & 8.84449713737402 \tabularnewline
24 & 9.14484046179746 \tabularnewline
25 & 9.24932429964481 \tabularnewline
26 & 9.79679727033635 \tabularnewline
27 & 10.2633740269860 \tabularnewline
28 & 10.3190669237608 \tabularnewline
29 & 10.3889364229453 \tabularnewline
30 & 10.9233182808928 \tabularnewline
31 & 12.4385046704342 \tabularnewline
32 & 12.4559042613586 \tabularnewline
33 & 12.7379027446850 \tabularnewline
34 & 13.0859465167102 \tabularnewline
35 & 13.4612099618835 \tabularnewline
36 & 13.5073998026292 \tabularnewline
37 & 14.0164189435105 \tabularnewline
38 & 14.3912885718970 \tabularnewline
39 & 14.7637011071232 \tabularnewline
40 & 15.6316076178584 \tabularnewline
41 & 15.723826795461 \tabularnewline
42 & 15.8251255223825 \tabularnewline
43 & 19.1557298969079 \tabularnewline
44 & 22.1822000712283 \tabularnewline
45 & 23.6165150580646 \tabularnewline
46 & 24.7990771325046 \tabularnewline
47 & 25.0581987388767 \tabularnewline
48 & 32.7135379049812 \tabularnewline
49 & 35.9511110358936 \tabularnewline
50 & 37.9070147502445 \tabularnewline
51 & 47.515108829537 \tabularnewline
52 & 58.1162506945276 \tabularnewline
53 & 62.3543610990595 \tabularnewline
54 & 66.5046927196352 \tabularnewline
55 & 67.3167385760507 \tabularnewline
56 & 96.46840019713 \tabularnewline
57 & 100.882219742585 \tabularnewline
58 & 132.371302918782 \tabularnewline
59 & 201.190158639282 \tabularnewline
60 & 513.762410088595 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=500&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]2.50998007960223[/C][/ROW]
[ROW][C]2[/C][C]2.55147016443462[/C][/ROW]
[ROW][C]3[/C][C]2.62488094968135[/C][/ROW]
[ROW][C]4[/C][C]2.95972971738974[/C][/ROW]
[ROW][C]5[/C][C]3.39411254969542[/C][/ROW]
[ROW][C]6[/C][C]3.52278299076171[/C][/ROW]
[ROW][C]7[/C][C]3.75632799419859[/C][/ROW]
[ROW][C]8[/C][C]3.76696164036747[/C][/ROW]
[ROW][C]9[/C][C]4.51995575199581[/C][/ROW]
[ROW][C]10[/C][C]4.73392015141786[/C][/ROW]
[ROW][C]11[/C][C]4.9079010563827[/C][/ROW]
[ROW][C]12[/C][C]5.25071423713004[/C][/ROW]
[ROW][C]13[/C][C]5.3[/C][/ROW]
[ROW][C]14[/C][C]5.33104117410474[/C][/ROW]
[ROW][C]15[/C][C]5.4[/C][/ROW]
[ROW][C]16[/C][C]5.98080262172226[/C][/ROW]
[ROW][C]17[/C][C]6.22047838353215[/C][/ROW]
[ROW][C]18[/C][C]6.38278935889318[/C][/ROW]
[ROW][C]19[/C][C]6.57038811639008[/C][/ROW]
[ROW][C]20[/C][C]6.92977413024462[/C][/ROW]
[ROW][C]21[/C][C]7.64002617796562[/C][/ROW]
[ROW][C]22[/C][C]8.1182593038984[/C][/ROW]
[ROW][C]23[/C][C]8.84449713737402[/C][/ROW]
[ROW][C]24[/C][C]9.14484046179746[/C][/ROW]
[ROW][C]25[/C][C]9.24932429964481[/C][/ROW]
[ROW][C]26[/C][C]9.79679727033635[/C][/ROW]
[ROW][C]27[/C][C]10.2633740269860[/C][/ROW]
[ROW][C]28[/C][C]10.3190669237608[/C][/ROW]
[ROW][C]29[/C][C]10.3889364229453[/C][/ROW]
[ROW][C]30[/C][C]10.9233182808928[/C][/ROW]
[ROW][C]31[/C][C]12.4385046704342[/C][/ROW]
[ROW][C]32[/C][C]12.4559042613586[/C][/ROW]
[ROW][C]33[/C][C]12.7379027446850[/C][/ROW]
[ROW][C]34[/C][C]13.0859465167102[/C][/ROW]
[ROW][C]35[/C][C]13.4612099618835[/C][/ROW]
[ROW][C]36[/C][C]13.5073998026292[/C][/ROW]
[ROW][C]37[/C][C]14.0164189435105[/C][/ROW]
[ROW][C]38[/C][C]14.3912885718970[/C][/ROW]
[ROW][C]39[/C][C]14.7637011071232[/C][/ROW]
[ROW][C]40[/C][C]15.6316076178584[/C][/ROW]
[ROW][C]41[/C][C]15.723826795461[/C][/ROW]
[ROW][C]42[/C][C]15.8251255223825[/C][/ROW]
[ROW][C]43[/C][C]19.1557298969079[/C][/ROW]
[ROW][C]44[/C][C]22.1822000712283[/C][/ROW]
[ROW][C]45[/C][C]23.6165150580646[/C][/ROW]
[ROW][C]46[/C][C]24.7990771325046[/C][/ROW]
[ROW][C]47[/C][C]25.0581987388767[/C][/ROW]
[ROW][C]48[/C][C]32.7135379049812[/C][/ROW]
[ROW][C]49[/C][C]35.9511110358936[/C][/ROW]
[ROW][C]50[/C][C]37.9070147502445[/C][/ROW]
[ROW][C]51[/C][C]47.515108829537[/C][/ROW]
[ROW][C]52[/C][C]58.1162506945276[/C][/ROW]
[ROW][C]53[/C][C]62.3543610990595[/C][/ROW]
[ROW][C]54[/C][C]66.5046927196352[/C][/ROW]
[ROW][C]55[/C][C]67.3167385760507[/C][/ROW]
[ROW][C]56[/C][C]96.46840019713[/C][/ROW]
[ROW][C]57[/C][C]100.882219742585[/C][/ROW]
[ROW][C]58[/C][C]132.371302918782[/C][/ROW]
[ROW][C]59[/C][C]201.190158639282[/C][/ROW]
[ROW][C]60[/C][C]513.762410088595[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=500&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=500&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
12.50998007960223
22.55147016443462
32.62488094968135
42.95972971738974
53.39411254969542
63.52278299076171
73.75632799419859
83.76696164036747
94.51995575199581
104.73392015141786
114.9079010563827
125.25071423713004
135.3
145.33104117410474
155.4
165.98080262172226
176.22047838353215
186.38278935889318
196.57038811639008
206.92977413024462
217.64002617796562
228.1182593038984
238.84449713737402
249.14484046179746
259.24932429964481
269.79679727033635
2710.2633740269860
2810.3190669237608
2910.3889364229453
3010.9233182808928
3112.4385046704342
3212.4559042613586
3312.7379027446850
3413.0859465167102
3513.4612099618835
3613.5073998026292
3714.0164189435105
3814.3912885718970
3914.7637011071232
4015.6316076178584
4115.723826795461
4215.8251255223825
4319.1557298969079
4422.1822000712283
4523.6165150580646
4624.7990771325046
4725.0581987388767
4832.7135379049812
4935.9511110358936
5037.9070147502445
5147.515108829537
5258.1162506945276
5362.3543610990595
5466.5046927196352
5567.3167385760507
5696.46840019713
57100.882219742585
58132.371302918782
59201.190158639282
60513.762410088595


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')
}