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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 computationSun, 09 Nov 2008 10:35:59 -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/09/t12262522067o5k7t05a1cbnay.htm/, Retrieved Sun, 19 May 2024 09:15:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22790, Retrieved Sun, 19 May 2024 09:15:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

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] [Dendrogram - Bob ...] [2008-11-09 17:35:59] [0831954c833179c36e9320daee0825b5] [Current]
Feedback Forum
2008-11-19 12:13:26 [Bob Leysen] [reply] 
De grafiek is correct.
De gegevens zijn sterk verdeeld (in 2 stukken). Je kan blijven splitsen tot je bij 1 observatie komt.
Een dendrogram wordt meestal gebruikt voor niet tijdsreeksen. Vb. als er verschillende producten zijn kan je zien welke samenhoren.
2008-11-21 15:31:53 [Stijn Van de Velde] [reply] 
Het antwoord is juist, je conclusie ook.

De gelijkaardige waarnemingen worden hier per groep gesorteerd. Om te beginnen zie je dat de data in 2 grote groepen worden opgesplitst. Daarna worden ze nog verder opgesplitst in verschillende takken.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
641	12055	2411
550	12113	2361
542	9617	1924
629	12646	2487
687	13581	2675
612	12162	2296
588	10970	2102
567	11880	2322
564	11888	2274
570	12927	2501
635	12300	2435
591	12093	2273
634	12381	2455
576	12197	2329
352	9455	1897
508	13168	2608
586	13428	2712
666	11981	2322
694	11885	2283
651	11692	2241
655	12234	2417
734	14341	2829
648	13131	2601
678	12421	2321
816	14286	2769
591	12865	2457
564	11160	2143
743	14316	2764
694	14389	2789
729	14014	2680
749	13419	2537
539	12770	2683
569	13316	2700
693	15333	3098
581	14243	3015
507	13824	2878
613	14963	3011
443	13203	2612
523	12199	2419
597	15509	3097
534	14200	3013
523	15170	3397
559	14058	3423
431	13786	3299
538	14148	3066
612	16542	3918
428	13588	3154
522	15582	3335
531	15803	3462
426	14131	3019
410	12923	2832
551	15612	3301
556	16034	3343
460	16037	3464
289	14038	3017
392	15331	3201
401	15038	3135
399	17402	3550
355	14993	3247
338	16044	3442
379	16930	3536
334	15921	3385
322	14417	2997
450	15961	3403
486	17852	3900
422	16484	3776
406	14216	3198
420	17430	4022
432	17840	3845
418	17629	3818

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22790&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22790&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22790&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Summary of Dendrogram
LabelHeight
148.7544869729956
253.8237865631916
360.0832755431992
463.7338214765128
570.221079456243
671.2741187248218
773.9324015570981
878.0064099930256
978.873316146844
1086.9893982244582
1197.9642792042079
1299.121138007995
13105.714801802845
14107.335921293852
15113.916636186292
16115.731340653373
17129.170430052702
18134.052711262447
19135.624481565829
20138.463944700107
21165.005084548951
22165.595893668895
23169.304307334819
24189.365152184422
25195.849431962413
26200.481919384268
27213.554908516145
28217.042833420790
29221.657393289734
30242.957474679932
31244.188451815396
32245.434308930109
33248.064711264582
34248.781028215578
35251.143385339929
36263.926599467221
37280.876722024433
38285.478545603693
39307.840174281003
40322.855417949647
41338.530959550444
42348.363822681897
43352.970253704190
44362.102640809175
45383.242442681461
46417.008294375044
47472.630934239391
48474.87626807355
49481.110647154942
50498.249508761792
51506.414097006056
52565.357871200544
53596.680061504252
54861.968836740894
55885.041688058516
561144.39252278695
571148.55952092483
581261.44771108903
591449.20444157821
601622.2398856452
611816.06946366881
622353.69210483297
632879.81312163701
643518.17185606517
658144.32798603646
669976.051067628
6712849.9165507735
6829032.7566517776
6965670.2065159047

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 48.7544869729956 \tabularnewline
2 & 53.8237865631916 \tabularnewline
3 & 60.0832755431992 \tabularnewline
4 & 63.7338214765128 \tabularnewline
5 & 70.221079456243 \tabularnewline
6 & 71.2741187248218 \tabularnewline
7 & 73.9324015570981 \tabularnewline
8 & 78.0064099930256 \tabularnewline
9 & 78.873316146844 \tabularnewline
10 & 86.9893982244582 \tabularnewline
11 & 97.9642792042079 \tabularnewline
12 & 99.121138007995 \tabularnewline
13 & 105.714801802845 \tabularnewline
14 & 107.335921293852 \tabularnewline
15 & 113.916636186292 \tabularnewline
16 & 115.731340653373 \tabularnewline
17 & 129.170430052702 \tabularnewline
18 & 134.052711262447 \tabularnewline
19 & 135.624481565829 \tabularnewline
20 & 138.463944700107 \tabularnewline
21 & 165.005084548951 \tabularnewline
22 & 165.595893668895 \tabularnewline
23 & 169.304307334819 \tabularnewline
24 & 189.365152184422 \tabularnewline
25 & 195.849431962413 \tabularnewline
26 & 200.481919384268 \tabularnewline
27 & 213.554908516145 \tabularnewline
28 & 217.042833420790 \tabularnewline
29 & 221.657393289734 \tabularnewline
30 & 242.957474679932 \tabularnewline
31 & 244.188451815396 \tabularnewline
32 & 245.434308930109 \tabularnewline
33 & 248.064711264582 \tabularnewline
34 & 248.781028215578 \tabularnewline
35 & 251.143385339929 \tabularnewline
36 & 263.926599467221 \tabularnewline
37 & 280.876722024433 \tabularnewline
38 & 285.478545603693 \tabularnewline
39 & 307.840174281003 \tabularnewline
40 & 322.855417949647 \tabularnewline
41 & 338.530959550444 \tabularnewline
42 & 348.363822681897 \tabularnewline
43 & 352.970253704190 \tabularnewline
44 & 362.102640809175 \tabularnewline
45 & 383.242442681461 \tabularnewline
46 & 417.008294375044 \tabularnewline
47 & 472.630934239391 \tabularnewline
48 & 474.87626807355 \tabularnewline
49 & 481.110647154942 \tabularnewline
50 & 498.249508761792 \tabularnewline
51 & 506.414097006056 \tabularnewline
52 & 565.357871200544 \tabularnewline
53 & 596.680061504252 \tabularnewline
54 & 861.968836740894 \tabularnewline
55 & 885.041688058516 \tabularnewline
56 & 1144.39252278695 \tabularnewline
57 & 1148.55952092483 \tabularnewline
58 & 1261.44771108903 \tabularnewline
59 & 1449.20444157821 \tabularnewline
60 & 1622.2398856452 \tabularnewline
61 & 1816.06946366881 \tabularnewline
62 & 2353.69210483297 \tabularnewline
63 & 2879.81312163701 \tabularnewline
64 & 3518.17185606517 \tabularnewline
65 & 8144.32798603646 \tabularnewline
66 & 9976.051067628 \tabularnewline
67 & 12849.9165507735 \tabularnewline
68 & 29032.7566517776 \tabularnewline
69 & 65670.2065159047 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22790&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]48.7544869729956[/C][/ROW]
[ROW][C]2[/C][C]53.8237865631916[/C][/ROW]
[ROW][C]3[/C][C]60.0832755431992[/C][/ROW]
[ROW][C]4[/C][C]63.7338214765128[/C][/ROW]
[ROW][C]5[/C][C]70.221079456243[/C][/ROW]
[ROW][C]6[/C][C]71.2741187248218[/C][/ROW]
[ROW][C]7[/C][C]73.9324015570981[/C][/ROW]
[ROW][C]8[/C][C]78.0064099930256[/C][/ROW]
[ROW][C]9[/C][C]78.873316146844[/C][/ROW]
[ROW][C]10[/C][C]86.9893982244582[/C][/ROW]
[ROW][C]11[/C][C]97.9642792042079[/C][/ROW]
[ROW][C]12[/C][C]99.121138007995[/C][/ROW]
[ROW][C]13[/C][C]105.714801802845[/C][/ROW]
[ROW][C]14[/C][C]107.335921293852[/C][/ROW]
[ROW][C]15[/C][C]113.916636186292[/C][/ROW]
[ROW][C]16[/C][C]115.731340653373[/C][/ROW]
[ROW][C]17[/C][C]129.170430052702[/C][/ROW]
[ROW][C]18[/C][C]134.052711262447[/C][/ROW]
[ROW][C]19[/C][C]135.624481565829[/C][/ROW]
[ROW][C]20[/C][C]138.463944700107[/C][/ROW]
[ROW][C]21[/C][C]165.005084548951[/C][/ROW]
[ROW][C]22[/C][C]165.595893668895[/C][/ROW]
[ROW][C]23[/C][C]169.304307334819[/C][/ROW]
[ROW][C]24[/C][C]189.365152184422[/C][/ROW]
[ROW][C]25[/C][C]195.849431962413[/C][/ROW]
[ROW][C]26[/C][C]200.481919384268[/C][/ROW]
[ROW][C]27[/C][C]213.554908516145[/C][/ROW]
[ROW][C]28[/C][C]217.042833420790[/C][/ROW]
[ROW][C]29[/C][C]221.657393289734[/C][/ROW]
[ROW][C]30[/C][C]242.957474679932[/C][/ROW]
[ROW][C]31[/C][C]244.188451815396[/C][/ROW]
[ROW][C]32[/C][C]245.434308930109[/C][/ROW]
[ROW][C]33[/C][C]248.064711264582[/C][/ROW]
[ROW][C]34[/C][C]248.781028215578[/C][/ROW]
[ROW][C]35[/C][C]251.143385339929[/C][/ROW]
[ROW][C]36[/C][C]263.926599467221[/C][/ROW]
[ROW][C]37[/C][C]280.876722024433[/C][/ROW]
[ROW][C]38[/C][C]285.478545603693[/C][/ROW]
[ROW][C]39[/C][C]307.840174281003[/C][/ROW]
[ROW][C]40[/C][C]322.855417949647[/C][/ROW]
[ROW][C]41[/C][C]338.530959550444[/C][/ROW]
[ROW][C]42[/C][C]348.363822681897[/C][/ROW]
[ROW][C]43[/C][C]352.970253704190[/C][/ROW]
[ROW][C]44[/C][C]362.102640809175[/C][/ROW]
[ROW][C]45[/C][C]383.242442681461[/C][/ROW]
[ROW][C]46[/C][C]417.008294375044[/C][/ROW]
[ROW][C]47[/C][C]472.630934239391[/C][/ROW]
[ROW][C]48[/C][C]474.87626807355[/C][/ROW]
[ROW][C]49[/C][C]481.110647154942[/C][/ROW]
[ROW][C]50[/C][C]498.249508761792[/C][/ROW]
[ROW][C]51[/C][C]506.414097006056[/C][/ROW]
[ROW][C]52[/C][C]565.357871200544[/C][/ROW]
[ROW][C]53[/C][C]596.680061504252[/C][/ROW]
[ROW][C]54[/C][C]861.968836740894[/C][/ROW]
[ROW][C]55[/C][C]885.041688058516[/C][/ROW]
[ROW][C]56[/C][C]1144.39252278695[/C][/ROW]
[ROW][C]57[/C][C]1148.55952092483[/C][/ROW]
[ROW][C]58[/C][C]1261.44771108903[/C][/ROW]
[ROW][C]59[/C][C]1449.20444157821[/C][/ROW]
[ROW][C]60[/C][C]1622.2398856452[/C][/ROW]
[ROW][C]61[/C][C]1816.06946366881[/C][/ROW]
[ROW][C]62[/C][C]2353.69210483297[/C][/ROW]
[ROW][C]63[/C][C]2879.81312163701[/C][/ROW]
[ROW][C]64[/C][C]3518.17185606517[/C][/ROW]
[ROW][C]65[/C][C]8144.32798603646[/C][/ROW]
[ROW][C]66[/C][C]9976.051067628[/C][/ROW]
[ROW][C]67[/C][C]12849.9165507735[/C][/ROW]
[ROW][C]68[/C][C]29032.7566517776[/C][/ROW]
[ROW][C]69[/C][C]65670.2065159047[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22790&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22790&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
148.7544869729956
253.8237865631916
360.0832755431992
463.7338214765128
570.221079456243
671.2741187248218
773.9324015570981
878.0064099930256
978.873316146844
1086.9893982244582
1197.9642792042079
1299.121138007995
13105.714801802845
14107.335921293852
15113.916636186292
16115.731340653373
17129.170430052702
18134.052711262447
19135.624481565829
20138.463944700107
21165.005084548951
22165.595893668895
23169.304307334819
24189.365152184422
25195.849431962413
26200.481919384268
27213.554908516145
28217.042833420790
29221.657393289734
30242.957474679932
31244.188451815396
32245.434308930109
33248.064711264582
34248.781028215578
35251.143385339929
36263.926599467221
37280.876722024433
38285.478545603693
39307.840174281003
40322.855417949647
41338.530959550444
42348.363822681897
43352.970253704190
44362.102640809175
45383.242442681461
46417.008294375044
47472.630934239391
48474.87626807355
49481.110647154942
50498.249508761792
51506.414097006056
52565.357871200544
53596.680061504252
54861.968836740894
55885.041688058516
561144.39252278695
571148.55952092483
581261.44771108903
591449.20444157821
601622.2398856452
611816.06946366881
622353.69210483297
632879.81312163701
643518.17185606517
658144.32798603646
669976.051067628
6712849.9165507735
6829032.7566517776
6965670.2065159047


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')
}