FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationSun, 09 Nov 2008 09:10:03 -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/t1226247056opsdqs1ixgbbgsb.htm/, Retrieved Sun, 19 May 2024 12:38:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22770, Retrieved Sun, 19 May 2024 12:38:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsVan Dooren Leen
Estimated Impact199

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] [Various EDA topic...] [2008-11-09 16:10:03] [d175f84d503eb4f2a43145d5e67795b5] [Current]
Feedback Forum
2008-11-16 15:30:23 [Steven Vercammen] [reply] 
Er werd geen uitleg gegeven omdat dat dit nog niet besproken was tijdens het college en er geen info over te vinden is in het e-handbook. Bij hierarchical clustering tekent men een dendrogram. Hierinis het zo dat de tijdreeks telkens wordt opgesplitst zodat er telkens kleine clusters ontstaan. Hier kan men uit afleiden welke observaties 'bij elkaar horen'. Het dendrogram wordt louter exploratief gebruikt.
2008-11-16 15:55:50 [074508d5a5a3592082de3e836d27af7d] [reply] 
Het nut van een dendrogram is dat we kunnen zien welke gegevens in 1 groep zitten en welke we dus anders moeten behandelen.
2008-11-16 16:30:32 [006ad2c49b6a7c2ad6ab685cfc1dae56] [reply] 
Ik had bij deze grafiek geen uitleg gegeven. het dendrogram wordt gebruikt om na te gaan of er in de periodes groepen kunnen gemaakt worden die gelijkaardig zijn. In het begin worden de gegevens gesplitst in twee delen en van hieruit worden verdere groepen gevormd (clusters).

2008-11-19 10:47:04 [Toon Wouters] [reply] 
De dendogram maakt het mogelijk om te kijken of in de periodes groepen worden gemaakt die op elkaar trekken. Wanneer de tijdreeksen opgesplitst worden in takken vb 2 dan zijn deze periodes gelijkaardig.
2008-11-24 11:46:14 [Anouk Greeve] [reply] 
Jammer dat er geen interpretatie gegeven wordt. Het nut van een dendrogram is dat we kunnen zien welke gegevens in 1 groep zitten en welke we dus anders moeten behandelen. We kunnen vaststellen dat de waarden van de periodes die in dezelfde kluster liggen, rond dezelfde hoogte liggen en dus dezelfde gegevens bevatten.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
519	127	392
517	123	394
510	118	392
509	114	396
501	108	392
507	111	396
569	151	419
580	159	421
578	158	420
565	148	418
547	138	410
555	137	418
562	136	426
561	133	428
555	126	430
544	120	424
537	114	423
543	116	427
594	153	441
611	162	449
613	161	452
611	149	462
594	139	455
595	135	461
591	130	461
589	127	463
584	122	462
573	117	456
567	112	455
569	113	456
621	149	472
629	157	472
628	157	471
612	147	465
595	137	459
597	132	465
593	125	468
590	123	467
580	117	463
574	114	460
573	111	462
573	112	461
620	144	476
626	150	476
620	149	471
588	134	453
566	123	443
557	116	442
561	117	444
549	111	438
532	105	427
526	102	424
511	95	416
499	93	406
555	124	431
565	130	434
542	124	418
527	115	412
510	106	404
514	105	409
517	105	412
508	101	406
493	95	398
490	93	397
469	84	385
478	87	390
528	116	413
534	120	413
518	117	401
506	109	397

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22770&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22770&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22770&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Summary of Dendrogram
LabelHeight
11.41421356237310
21.41421356237310
31.41421356237310
41.73205080756888
52.23606797749979
62.44948974278318
72.44948974278318
82.44948974278318
92.82842712474619
103.65602689891371
113.74165738677394
123.74165738677394
133.74165738677394
143.74165738677394
153.74165738677394
164.12310562561766
174.24264068711928
184.58257569495584
194.89897948556636
205.09901951359278
215.09901951359278
225.53125745811468
235.74456264653803
246.48074069840786
256.96564801457551
267.34846922834953
278.20407816807507
288.48528137423857
299.00353107304067
309.47161567483146
3110.0035541233253
3210.0436084811547
3310.7009376651595
3410.7238052947636
3510.9198183276202
3611.352162112529
3711.3578166916005
3811.7688290727508
3911.9339157331054
4012.2642459334231
4112.3828431695042
4213.2567139436797
4313.5432442106297
4414.0367549301043
4514.7017043493017
4616.6511101865354
4719.1887274389745
4821.5136604490006
4924.4873530190255
5025.3853212333016
5126.5044481470131
5228.2189872358057
5336.5424602768386
5437.2045360954518
5539.0686494559738
5639.5824941977336
5740.7455027169033
5841.9742545325414
5948.030064668399
6070.4703066696427
6174.7229657882031
6287.5786186610769
63133.288365382396
64137.743542236795
65144.620610233962
66217.481031826518
67386.419423258650
68717.95618427546
691667.04090043997

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 1.41421356237310 \tabularnewline
2 & 1.41421356237310 \tabularnewline
3 & 1.41421356237310 \tabularnewline
4 & 1.73205080756888 \tabularnewline
5 & 2.23606797749979 \tabularnewline
6 & 2.44948974278318 \tabularnewline
7 & 2.44948974278318 \tabularnewline
8 & 2.44948974278318 \tabularnewline
9 & 2.82842712474619 \tabularnewline
10 & 3.65602689891371 \tabularnewline
11 & 3.74165738677394 \tabularnewline
12 & 3.74165738677394 \tabularnewline
13 & 3.74165738677394 \tabularnewline
14 & 3.74165738677394 \tabularnewline
15 & 3.74165738677394 \tabularnewline
16 & 4.12310562561766 \tabularnewline
17 & 4.24264068711928 \tabularnewline
18 & 4.58257569495584 \tabularnewline
19 & 4.89897948556636 \tabularnewline
20 & 5.09901951359278 \tabularnewline
21 & 5.09901951359278 \tabularnewline
22 & 5.53125745811468 \tabularnewline
23 & 5.74456264653803 \tabularnewline
24 & 6.48074069840786 \tabularnewline
25 & 6.96564801457551 \tabularnewline
26 & 7.34846922834953 \tabularnewline
27 & 8.20407816807507 \tabularnewline
28 & 8.48528137423857 \tabularnewline
29 & 9.00353107304067 \tabularnewline
30 & 9.47161567483146 \tabularnewline
31 & 10.0035541233253 \tabularnewline
32 & 10.0436084811547 \tabularnewline
33 & 10.7009376651595 \tabularnewline
34 & 10.7238052947636 \tabularnewline
35 & 10.9198183276202 \tabularnewline
36 & 11.352162112529 \tabularnewline
37 & 11.3578166916005 \tabularnewline
38 & 11.7688290727508 \tabularnewline
39 & 11.9339157331054 \tabularnewline
40 & 12.2642459334231 \tabularnewline
41 & 12.3828431695042 \tabularnewline
42 & 13.2567139436797 \tabularnewline
43 & 13.5432442106297 \tabularnewline
44 & 14.0367549301043 \tabularnewline
45 & 14.7017043493017 \tabularnewline
46 & 16.6511101865354 \tabularnewline
47 & 19.1887274389745 \tabularnewline
48 & 21.5136604490006 \tabularnewline
49 & 24.4873530190255 \tabularnewline
50 & 25.3853212333016 \tabularnewline
51 & 26.5044481470131 \tabularnewline
52 & 28.2189872358057 \tabularnewline
53 & 36.5424602768386 \tabularnewline
54 & 37.2045360954518 \tabularnewline
55 & 39.0686494559738 \tabularnewline
56 & 39.5824941977336 \tabularnewline
57 & 40.7455027169033 \tabularnewline
58 & 41.9742545325414 \tabularnewline
59 & 48.030064668399 \tabularnewline
60 & 70.4703066696427 \tabularnewline
61 & 74.7229657882031 \tabularnewline
62 & 87.5786186610769 \tabularnewline
63 & 133.288365382396 \tabularnewline
64 & 137.743542236795 \tabularnewline
65 & 144.620610233962 \tabularnewline
66 & 217.481031826518 \tabularnewline
67 & 386.419423258650 \tabularnewline
68 & 717.95618427546 \tabularnewline
69 & 1667.04090043997 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22770&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]1.41421356237310[/C][/ROW]
[ROW][C]2[/C][C]1.41421356237310[/C][/ROW]
[ROW][C]3[/C][C]1.41421356237310[/C][/ROW]
[ROW][C]4[/C][C]1.73205080756888[/C][/ROW]
[ROW][C]5[/C][C]2.23606797749979[/C][/ROW]
[ROW][C]6[/C][C]2.44948974278318[/C][/ROW]
[ROW][C]7[/C][C]2.44948974278318[/C][/ROW]
[ROW][C]8[/C][C]2.44948974278318[/C][/ROW]
[ROW][C]9[/C][C]2.82842712474619[/C][/ROW]
[ROW][C]10[/C][C]3.65602689891371[/C][/ROW]
[ROW][C]11[/C][C]3.74165738677394[/C][/ROW]
[ROW][C]12[/C][C]3.74165738677394[/C][/ROW]
[ROW][C]13[/C][C]3.74165738677394[/C][/ROW]
[ROW][C]14[/C][C]3.74165738677394[/C][/ROW]
[ROW][C]15[/C][C]3.74165738677394[/C][/ROW]
[ROW][C]16[/C][C]4.12310562561766[/C][/ROW]
[ROW][C]17[/C][C]4.24264068711928[/C][/ROW]
[ROW][C]18[/C][C]4.58257569495584[/C][/ROW]
[ROW][C]19[/C][C]4.89897948556636[/C][/ROW]
[ROW][C]20[/C][C]5.09901951359278[/C][/ROW]
[ROW][C]21[/C][C]5.09901951359278[/C][/ROW]
[ROW][C]22[/C][C]5.53125745811468[/C][/ROW]
[ROW][C]23[/C][C]5.74456264653803[/C][/ROW]
[ROW][C]24[/C][C]6.48074069840786[/C][/ROW]
[ROW][C]25[/C][C]6.96564801457551[/C][/ROW]
[ROW][C]26[/C][C]7.34846922834953[/C][/ROW]
[ROW][C]27[/C][C]8.20407816807507[/C][/ROW]
[ROW][C]28[/C][C]8.48528137423857[/C][/ROW]
[ROW][C]29[/C][C]9.00353107304067[/C][/ROW]
[ROW][C]30[/C][C]9.47161567483146[/C][/ROW]
[ROW][C]31[/C][C]10.0035541233253[/C][/ROW]
[ROW][C]32[/C][C]10.0436084811547[/C][/ROW]
[ROW][C]33[/C][C]10.7009376651595[/C][/ROW]
[ROW][C]34[/C][C]10.7238052947636[/C][/ROW]
[ROW][C]35[/C][C]10.9198183276202[/C][/ROW]
[ROW][C]36[/C][C]11.352162112529[/C][/ROW]
[ROW][C]37[/C][C]11.3578166916005[/C][/ROW]
[ROW][C]38[/C][C]11.7688290727508[/C][/ROW]
[ROW][C]39[/C][C]11.9339157331054[/C][/ROW]
[ROW][C]40[/C][C]12.2642459334231[/C][/ROW]
[ROW][C]41[/C][C]12.3828431695042[/C][/ROW]
[ROW][C]42[/C][C]13.2567139436797[/C][/ROW]
[ROW][C]43[/C][C]13.5432442106297[/C][/ROW]
[ROW][C]44[/C][C]14.0367549301043[/C][/ROW]
[ROW][C]45[/C][C]14.7017043493017[/C][/ROW]
[ROW][C]46[/C][C]16.6511101865354[/C][/ROW]
[ROW][C]47[/C][C]19.1887274389745[/C][/ROW]
[ROW][C]48[/C][C]21.5136604490006[/C][/ROW]
[ROW][C]49[/C][C]24.4873530190255[/C][/ROW]
[ROW][C]50[/C][C]25.3853212333016[/C][/ROW]
[ROW][C]51[/C][C]26.5044481470131[/C][/ROW]
[ROW][C]52[/C][C]28.2189872358057[/C][/ROW]
[ROW][C]53[/C][C]36.5424602768386[/C][/ROW]
[ROW][C]54[/C][C]37.2045360954518[/C][/ROW]
[ROW][C]55[/C][C]39.0686494559738[/C][/ROW]
[ROW][C]56[/C][C]39.5824941977336[/C][/ROW]
[ROW][C]57[/C][C]40.7455027169033[/C][/ROW]
[ROW][C]58[/C][C]41.9742545325414[/C][/ROW]
[ROW][C]59[/C][C]48.030064668399[/C][/ROW]
[ROW][C]60[/C][C]70.4703066696427[/C][/ROW]
[ROW][C]61[/C][C]74.7229657882031[/C][/ROW]
[ROW][C]62[/C][C]87.5786186610769[/C][/ROW]
[ROW][C]63[/C][C]133.288365382396[/C][/ROW]
[ROW][C]64[/C][C]137.743542236795[/C][/ROW]
[ROW][C]65[/C][C]144.620610233962[/C][/ROW]
[ROW][C]66[/C][C]217.481031826518[/C][/ROW]
[ROW][C]67[/C][C]386.419423258650[/C][/ROW]
[ROW][C]68[/C][C]717.95618427546[/C][/ROW]
[ROW][C]69[/C][C]1667.04090043997[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22770&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22770&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
11.41421356237310
21.41421356237310
31.41421356237310
41.73205080756888
52.23606797749979
62.44948974278318
72.44948974278318
82.44948974278318
92.82842712474619
103.65602689891371
113.74165738677394
123.74165738677394
133.74165738677394
143.74165738677394
153.74165738677394
164.12310562561766
174.24264068711928
184.58257569495584
194.89897948556636
205.09901951359278
215.09901951359278
225.53125745811468
235.74456264653803
246.48074069840786
256.96564801457551
267.34846922834953
278.20407816807507
288.48528137423857
299.00353107304067
309.47161567483146
3110.0035541233253
3210.0436084811547
3310.7009376651595
3410.7238052947636
3510.9198183276202
3611.352162112529
3711.3578166916005
3811.7688290727508
3911.9339157331054
4012.2642459334231
4112.3828431695042
4213.2567139436797
4313.5432442106297
4414.0367549301043
4514.7017043493017
4616.6511101865354
4719.1887274389745
4821.5136604490006
4924.4873530190255
5025.3853212333016
5126.5044481470131
5228.2189872358057
5336.5424602768386
5437.2045360954518
5539.0686494559738
5639.5824941977336
5740.7455027169033
5841.9742545325414
5948.030064668399
6070.4703066696427
6174.7229657882031
6287.5786186610769
63133.288365382396
64137.743542236795
65144.620610233962
66217.481031826518
67386.419423258650
68717.95618427546
691667.04090043997


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
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')
}