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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 computationWed, 05 Dec 2007 16:20:45 -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/Dec/06/t11968961896rr4759aqtj94rx.htm/, Retrieved Fri, 03 May 2024 08:52:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=14352, Retrieved Fri, 03 May 2024 08:52:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordshierarchical clustering
Estimated Impact216

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Hierarchical Clustering] [paper] [2007-12-05 23:20:45] [cde48c70ed84dc1a249f375f4ed54f97] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,9383	90,8	15	467.037
0,9217	96,4	3	460.070
0,9095	90	2	447.988
0,892	92,1	-2	442.867
0,8742	97,2	1	436.087
0,8532	95,1	1	431.328
0,8607	88,5	-1	484.015
0,9005	91	-6	509.673
0,9111	90,5	-13	512.927
0,9059	75	-25	502.831
0,8883	66,3	-26	470.984
0,8924	66	-9	471.067
0,8833	68,4	1	476.049
0,87	70,6	3	474.605
0,8758	83,9	6	470.439
0,8858	90,1	2	461.251
0,917	90,6	5	454.724
0,9554	87,1	5	455.626
0,9922	90,8	0	516.847
0,9778	94,1	-5	525.192
0,9808	99,8	-4	522.975
0,9811	96,8	-2	518.585
1,0014	87	-1	509.239
1,0183	96,3	-8	512.238
1,0622	107,1	-16	519.164
1,0773	115,2	-19	517.009
1,0807	106,1	-28	509.933
1,0848	89,5	-11	509.127
1,1582	91,3	-4	500.857
1,1663	97,6	-9	506.971
1,1372	100,7	-12	569.323
1,1139	104,6	-10	579.714
1,1222	94,7	-2	577.992
1,1692	101,8	-13	565.464
1,1702	102,5	0	547.344
1,2286	105,3	0	554.788
1,2613	110,3	4	562.325
1,2646	109,8	7	560.854
1,2262	117,3	5	555.332
1,1985	118,8	2	543.599
1,2007	131,3	-2	536.662
1,2138	125,9	6	542.722
1,2266	133,1	-3	593.530
1,2176	147	1	610.763
1,2218	145,8	0	612.613
1,249	164,4	-7	611.324
1,2991	149,8	-6	594.167
1,3408	137,7	-4	595.454
1,3119	151,7	-4	590.865
1,3014	156,8	-2	589.379
1,3201	180	2	584.428
1,2938	180,4	-5	573.100
1,2694	170,4	-15	567.456
1,2165	191,6	-16	569.028
1,2037	199,5	-18	620.735
1,2292	218,2	-13	628.884
1,2256	217,5	-23	628.232
1,2015	205	-10	612.117
1,1786	194	-10	595.404
1,1856	199,3	-6	597.141
1,2103	219,3	-3	593.408
1,1938	211,1	-4	590.072
1,202	215,2	-7	579.799
1,2271	240,2	-7	574.205
1,277	242,2	-7	572.775
1,265	240,7	-3	572.942
1,2684	255,4	0	619.567
1,2811	253	-5	625.809
1,2727	218,2	-3	619.916
1,2611	203,7	3	587.625
1,2881	205,6	2	565.742
1,3213	215,6	-7	557.274

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=14352&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=14352&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14352&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
12.42126364528939
22.45914416210197
33.3053461074447
43.37843926836047
53.61456478154701
64.13556586212811
74.3027163327368
84.41250174957473
94.84682255279545
105.08672956230227
115.20178065665981
125.51844117482469
135.68085381698912
146.4186086350548
156.48737618841393
166.82897849242475
176.86346982218178
187.39933958551287
197.95339842834492
208.196301793492
218.35001349040824
228.60105964301368
238.90248577701756
248.90893754888878
259.80562401037406
2610.0456516443683
2711.3909915184057
2811.8400806690664
2911.8545037200602
3012.2652875871804
3112.8442731553794
3212.9815225932862
3313.3223224585655
3413.6578408241457
3514.5142850376120
3614.7622907842403
3715.4027296537010
3815.8967960998435
3916.7914058688491
4016.897410352152
4118.4190402098505
4220.0538987731271
4320.329848432723
4420.8893943003728
4521.2817758283936
4622.3163092558947
4723.1262794693488
4824.5433190698692
4925.2426437123351
5031.2545020527887
5132.3698849091046
5234.62036595797
5335.8634660427677
5436.6595593436927
5538.4391821824206
5643.4855952742598
5751.2501794156487
5857.1720923415957
5962.0016853245011
6070.0514744535924
6181.9324801989003
6293.4312500314531
63101.416339970273
64101.94634944147
65115.723021947692
66149.419927511374
67251.119794753843
68388.458796326714
69555.32721776536
701147.76902583749
712779.65320960448

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 2.42126364528939 \tabularnewline
2 & 2.45914416210197 \tabularnewline
3 & 3.3053461074447 \tabularnewline
4 & 3.37843926836047 \tabularnewline
5 & 3.61456478154701 \tabularnewline
6 & 4.13556586212811 \tabularnewline
7 & 4.3027163327368 \tabularnewline
8 & 4.41250174957473 \tabularnewline
9 & 4.84682255279545 \tabularnewline
10 & 5.08672956230227 \tabularnewline
11 & 5.20178065665981 \tabularnewline
12 & 5.51844117482469 \tabularnewline
13 & 5.68085381698912 \tabularnewline
14 & 6.4186086350548 \tabularnewline
15 & 6.48737618841393 \tabularnewline
16 & 6.82897849242475 \tabularnewline
17 & 6.86346982218178 \tabularnewline
18 & 7.39933958551287 \tabularnewline
19 & 7.95339842834492 \tabularnewline
20 & 8.196301793492 \tabularnewline
21 & 8.35001349040824 \tabularnewline
22 & 8.60105964301368 \tabularnewline
23 & 8.90248577701756 \tabularnewline
24 & 8.90893754888878 \tabularnewline
25 & 9.80562401037406 \tabularnewline
26 & 10.0456516443683 \tabularnewline
27 & 11.3909915184057 \tabularnewline
28 & 11.8400806690664 \tabularnewline
29 & 11.8545037200602 \tabularnewline
30 & 12.2652875871804 \tabularnewline
31 & 12.8442731553794 \tabularnewline
32 & 12.9815225932862 \tabularnewline
33 & 13.3223224585655 \tabularnewline
34 & 13.6578408241457 \tabularnewline
35 & 14.5142850376120 \tabularnewline
36 & 14.7622907842403 \tabularnewline
37 & 15.4027296537010 \tabularnewline
38 & 15.8967960998435 \tabularnewline
39 & 16.7914058688491 \tabularnewline
40 & 16.897410352152 \tabularnewline
41 & 18.4190402098505 \tabularnewline
42 & 20.0538987731271 \tabularnewline
43 & 20.329848432723 \tabularnewline
44 & 20.8893943003728 \tabularnewline
45 & 21.2817758283936 \tabularnewline
46 & 22.3163092558947 \tabularnewline
47 & 23.1262794693488 \tabularnewline
48 & 24.5433190698692 \tabularnewline
49 & 25.2426437123351 \tabularnewline
50 & 31.2545020527887 \tabularnewline
51 & 32.3698849091046 \tabularnewline
52 & 34.62036595797 \tabularnewline
53 & 35.8634660427677 \tabularnewline
54 & 36.6595593436927 \tabularnewline
55 & 38.4391821824206 \tabularnewline
56 & 43.4855952742598 \tabularnewline
57 & 51.2501794156487 \tabularnewline
58 & 57.1720923415957 \tabularnewline
59 & 62.0016853245011 \tabularnewline
60 & 70.0514744535924 \tabularnewline
61 & 81.9324801989003 \tabularnewline
62 & 93.4312500314531 \tabularnewline
63 & 101.416339970273 \tabularnewline
64 & 101.94634944147 \tabularnewline
65 & 115.723021947692 \tabularnewline
66 & 149.419927511374 \tabularnewline
67 & 251.119794753843 \tabularnewline
68 & 388.458796326714 \tabularnewline
69 & 555.32721776536 \tabularnewline
70 & 1147.76902583749 \tabularnewline
71 & 2779.65320960448 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14352&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]2.42126364528939[/C][/ROW]
[ROW][C]2[/C][C]2.45914416210197[/C][/ROW]
[ROW][C]3[/C][C]3.3053461074447[/C][/ROW]
[ROW][C]4[/C][C]3.37843926836047[/C][/ROW]
[ROW][C]5[/C][C]3.61456478154701[/C][/ROW]
[ROW][C]6[/C][C]4.13556586212811[/C][/ROW]
[ROW][C]7[/C][C]4.3027163327368[/C][/ROW]
[ROW][C]8[/C][C]4.41250174957473[/C][/ROW]
[ROW][C]9[/C][C]4.84682255279545[/C][/ROW]
[ROW][C]10[/C][C]5.08672956230227[/C][/ROW]
[ROW][C]11[/C][C]5.20178065665981[/C][/ROW]
[ROW][C]12[/C][C]5.51844117482469[/C][/ROW]
[ROW][C]13[/C][C]5.68085381698912[/C][/ROW]
[ROW][C]14[/C][C]6.4186086350548[/C][/ROW]
[ROW][C]15[/C][C]6.48737618841393[/C][/ROW]
[ROW][C]16[/C][C]6.82897849242475[/C][/ROW]
[ROW][C]17[/C][C]6.86346982218178[/C][/ROW]
[ROW][C]18[/C][C]7.39933958551287[/C][/ROW]
[ROW][C]19[/C][C]7.95339842834492[/C][/ROW]
[ROW][C]20[/C][C]8.196301793492[/C][/ROW]
[ROW][C]21[/C][C]8.35001349040824[/C][/ROW]
[ROW][C]22[/C][C]8.60105964301368[/C][/ROW]
[ROW][C]23[/C][C]8.90248577701756[/C][/ROW]
[ROW][C]24[/C][C]8.90893754888878[/C][/ROW]
[ROW][C]25[/C][C]9.80562401037406[/C][/ROW]
[ROW][C]26[/C][C]10.0456516443683[/C][/ROW]
[ROW][C]27[/C][C]11.3909915184057[/C][/ROW]
[ROW][C]28[/C][C]11.8400806690664[/C][/ROW]
[ROW][C]29[/C][C]11.8545037200602[/C][/ROW]
[ROW][C]30[/C][C]12.2652875871804[/C][/ROW]
[ROW][C]31[/C][C]12.8442731553794[/C][/ROW]
[ROW][C]32[/C][C]12.9815225932862[/C][/ROW]
[ROW][C]33[/C][C]13.3223224585655[/C][/ROW]
[ROW][C]34[/C][C]13.6578408241457[/C][/ROW]
[ROW][C]35[/C][C]14.5142850376120[/C][/ROW]
[ROW][C]36[/C][C]14.7622907842403[/C][/ROW]
[ROW][C]37[/C][C]15.4027296537010[/C][/ROW]
[ROW][C]38[/C][C]15.8967960998435[/C][/ROW]
[ROW][C]39[/C][C]16.7914058688491[/C][/ROW]
[ROW][C]40[/C][C]16.897410352152[/C][/ROW]
[ROW][C]41[/C][C]18.4190402098505[/C][/ROW]
[ROW][C]42[/C][C]20.0538987731271[/C][/ROW]
[ROW][C]43[/C][C]20.329848432723[/C][/ROW]
[ROW][C]44[/C][C]20.8893943003728[/C][/ROW]
[ROW][C]45[/C][C]21.2817758283936[/C][/ROW]
[ROW][C]46[/C][C]22.3163092558947[/C][/ROW]
[ROW][C]47[/C][C]23.1262794693488[/C][/ROW]
[ROW][C]48[/C][C]24.5433190698692[/C][/ROW]
[ROW][C]49[/C][C]25.2426437123351[/C][/ROW]
[ROW][C]50[/C][C]31.2545020527887[/C][/ROW]
[ROW][C]51[/C][C]32.3698849091046[/C][/ROW]
[ROW][C]52[/C][C]34.62036595797[/C][/ROW]
[ROW][C]53[/C][C]35.8634660427677[/C][/ROW]
[ROW][C]54[/C][C]36.6595593436927[/C][/ROW]
[ROW][C]55[/C][C]38.4391821824206[/C][/ROW]
[ROW][C]56[/C][C]43.4855952742598[/C][/ROW]
[ROW][C]57[/C][C]51.2501794156487[/C][/ROW]
[ROW][C]58[/C][C]57.1720923415957[/C][/ROW]
[ROW][C]59[/C][C]62.0016853245011[/C][/ROW]
[ROW][C]60[/C][C]70.0514744535924[/C][/ROW]
[ROW][C]61[/C][C]81.9324801989003[/C][/ROW]
[ROW][C]62[/C][C]93.4312500314531[/C][/ROW]
[ROW][C]63[/C][C]101.416339970273[/C][/ROW]
[ROW][C]64[/C][C]101.94634944147[/C][/ROW]
[ROW][C]65[/C][C]115.723021947692[/C][/ROW]
[ROW][C]66[/C][C]149.419927511374[/C][/ROW]
[ROW][C]67[/C][C]251.119794753843[/C][/ROW]
[ROW][C]68[/C][C]388.458796326714[/C][/ROW]
[ROW][C]69[/C][C]555.32721776536[/C][/ROW]
[ROW][C]70[/C][C]1147.76902583749[/C][/ROW]
[ROW][C]71[/C][C]2779.65320960448[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14352&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14352&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
12.42126364528939
22.45914416210197
33.3053461074447
43.37843926836047
53.61456478154701
64.13556586212811
74.3027163327368
84.41250174957473
94.84682255279545
105.08672956230227
115.20178065665981
125.51844117482469
135.68085381698912
146.4186086350548
156.48737618841393
166.82897849242475
176.86346982218178
187.39933958551287
197.95339842834492
208.196301793492
218.35001349040824
228.60105964301368
238.90248577701756
248.90893754888878
259.80562401037406
2610.0456516443683
2711.3909915184057
2811.8400806690664
2911.8545037200602
3012.2652875871804
3112.8442731553794
3212.9815225932862
3313.3223224585655
3413.6578408241457
3514.5142850376120
3614.7622907842403
3715.4027296537010
3815.8967960998435
3916.7914058688491
4016.897410352152
4118.4190402098505
4220.0538987731271
4320.329848432723
4420.8893943003728
4521.2817758283936
4622.3163092558947
4723.1262794693488
4824.5433190698692
4925.2426437123351
5031.2545020527887
5132.3698849091046
5234.62036595797
5335.8634660427677
5436.6595593436927
5538.4391821824206
5643.4855952742598
5751.2501794156487
5857.1720923415957
5962.0016853245011
6070.0514744535924
6181.9324801989003
6293.4312500314531
63101.416339970273
64101.94634944147
65115.723021947692
66149.419927511374
67251.119794753843
68388.458796326714
69555.32721776536
701147.76902583749
712779.65320960448


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')
}