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of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationWed, 12 Nov 2008 14:21:39 -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/12/t122652501016a6dxfrb7goosr.htm/, Retrieved Mon, 20 May 2024 05:21:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24448, Retrieved Mon, 20 May 2024 05:21:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsHierarchial Clustering
Estimated Impact145
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Hierarchical Clustering] [Hierarchial Clust...] [2008-11-12 21:21:39] [3bdbbe597ac6c61989658933956ee6ac] [Current]
Feedback Forum
2008-11-14 15:09:48 [c798c834ef86cb6aaf2fcb10ea683230] [reply
Het dendogram is een grafische voorstelling van de tijdsreeks die opgesplits wordt in 2 delen. Elke cluster wordt telkens opnieuw onderverdeeld totdat je in 1 enkele periode terechtkomt.
Er is niet echt een patroon terug te vinden in de clusters. In elke cluster kan elke periode voorkomen.
2008-11-23 16:40:22 [Peter Van Doninck] [reply
De student heeft een correct dendogram getekend. Dit stelt grafisch bepaalde clusters voor. Gegevens die gelijkaardig zijn, worden bij elkaar gegroepeerd. Hoe meer gegevens gelijkaardig zijn, hoe langer de 'lijn' die naar beneden gaat. Op het einde van de figuur zien we dat er vel categorieën gevormd worden. Deze categorieën kunnen gebruikt worden om vragen uit te distilleren, die dan onderzocht kunnen worden om duidelijke conclusies te trekken.
2008-11-24 14:31:58 [Vincent Dolhain] [reply
De dendogram is correct, conclusie ontbreekt. Er wordt hier gezocht naar clusters, beginnend van alles output wordt er getracht deze steeds verder onder te verdelen. In dit geval naar periodes met gelijkaardige resultaten

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Dataseries X:
110.1	66.9	91	97.1	98.1
117	108.8	120.7	112.6	98.3
129.6	113.2	127.9	113.8	114.8
113.5	105.5	112.4	107.8	107.8
113.3	77.8	93.1	103.2	107.9
110.1	102.1	107.5	103.3	112.7
107.4	97	107.3	101.2	100.2
110.1	95.5	114.8	107.7	96.9
112.5	99.3	120.8	110.4	96.6
106	86.4	112.2	101.9	95.5
117.6	92.4	123.3	115.9	96.9
117.8	85.7	100.6	89.9	99.7
113.5	61.9	86.7	88.6	105.1
121.2	104.9	123.6	117.2	106.1
130.4	107.9	125.3	123.9	106.2
115.2	95.6	111.1	100	103.9
117.9	79.8	98.4	103.6	109.2
110.7	94.8	102.3	94.1	110.5
107.6	93.7	105	98.7	98
124.3	108.1	128.2	119.5	94.1
115.1	96.9	124.7	112.7	90.2
112.5	88.8	116.1	104.4	89.5
127.9	106.7	131.2	124.7	91.2
117.4	86.8	97.7	89.1	98.2
119.3	69.8	88.8	97	103.7
130.4	110.9	132.8	121.6	103.9
126	105.4	113.9	118.8	106.5
125.4	99.2	112.6	114	107.2
130.5	84.4	104.3	111.5	111
115.9	87.2	107.5	97.2	111.8
108.7	91.9	106	102.5	101.5
124	97.9	117.3	113.4	95.3
119.4	94.5	123.1	109.8	92.7
118.6	85	114.3	104.9	93.5
131.3	100.3	132	126.1	96.2
111.1	78.7	92.3	80	102.1
124.8	65.8	93.7	96.8	102.3
132.3	104.8	121.3	117.2	127.9
126.7	96	113.6	112.3	130.8
131.7	103.3	116.3	117.3	134.9
130.9	82.9	98.3	111.1	141.9
122.1	91.4	111.9	102.2	124.6
113.2	94.5	109.3	104.3	118
133.6	109.3	133.2	122.9	115.1
119.2	92.1	118	107.6	111.2
129.4	99.3	131.6	121.3	113.5
131.4	109.6	134.1	131.5	115.2
117.1	87.5	96.7	89	119.4
130.5	73.1	99.8	104.4	116
132.3	110.7	128.3	128.9	115.7
140.8	111.6	134.9	135.9	121.1
137.5	110.7	130.7	133.3	120.8
128.6	84	107.3	121.3	125.2
126.7	101.6	121.6	120.5	124
120.8	102.1	120.6	120.4	119.1
139.3	113.9	140.5	137.9	119.2
128.6	99	124.8	126.1	113.9
131.3	100.4	129.9	133.2	113.3
136.3	109.5	159.4	151.1	116.8
128.8	93.1	111	105	114.8
133.2	77	110.1	119	119.2
136.3	108	132.7	140.4	117.8
151.1	119.9	135	156.6	122.5
145	105.9	118.6	137.1	125.1
134.4	78.2	94	122.7	125
135.7	100.3	117.9	125.8	125.1
128.7	102.2	114.7	139.3	121.2
129.2	97	113.6	134.9	118.9
138.6	101.3	130.6	149.2	109.8
132.7	89.2	117.1	132.3	109.2
132.5	93.3	123.2	149	109
137.3	88.5	106.1	117.2	110.9
127.1	62.2	87.9	116.2	112.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 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 & 8 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24448&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]8 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=24448&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24448&T=0

As an alternative you can also use a 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 time8 seconds
R Server'George Udny Yule' @ 72.249.76.132







Summary of Dendrogram
LabelHeight
13.55949434611153
25.22589705218157
35.85385019978483
46.01581249707803
56.43972049082879
66.53222779762003
77.29040465269247
87.42293742395827
97.7051930540383
107.75112895003045
117.97370679169983
128.001249902359
138.37675354776538
148.43445315358381
158.50058821494137
168.70804225988828
178.75328509760764
189.10878780157116
199.20244890347828
209.22074667891295
219.55981171362701
229.93931587182941
2310.6886076472774
2410.9219961545498
2511.0968463988649
2611.1022520238013
2711.5387679774247
2811.9812353286295
2912.1485238810851
3012.4630199539865
3112.5159897730863
3212.6933732419447
3312.7232071428551
3412.9327782434657
3513.2778010227598
3613.8706261456448
3716.1877658136178
3816.4432444264393
3916.4556563508604
4016.8257176018251
4117.3246036494697
4218.0926901504162
4318.5460971915411
4419.2980988184615
4519.7264910609359
4619.8626044828014
4720.5783867200517
4821.1548365802976
4922.0460266334611
5025.3856489850655
5125.9538630751251
5226.1483676792489
5328.0010737240974
5430.0519525358814
5531.3894886865014
5634.4427361073134
5735.7677815929308
5835.8075805043027
5936.1443808091085
6042.5006787151671
6143.438866683393
6244.847311681285
6351.1426642805709
6459.5282204812653
6566.7711550432266
6680.8024093157599
6792.4473793897082
68115.345813332353
69149.596098950422
70212.144261567956
71219.046075446177
72661.482319874866

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 3.55949434611153 \tabularnewline
2 & 5.22589705218157 \tabularnewline
3 & 5.85385019978483 \tabularnewline
4 & 6.01581249707803 \tabularnewline
5 & 6.43972049082879 \tabularnewline
6 & 6.53222779762003 \tabularnewline
7 & 7.29040465269247 \tabularnewline
8 & 7.42293742395827 \tabularnewline
9 & 7.7051930540383 \tabularnewline
10 & 7.75112895003045 \tabularnewline
11 & 7.97370679169983 \tabularnewline
12 & 8.001249902359 \tabularnewline
13 & 8.37675354776538 \tabularnewline
14 & 8.43445315358381 \tabularnewline
15 & 8.50058821494137 \tabularnewline
16 & 8.70804225988828 \tabularnewline
17 & 8.75328509760764 \tabularnewline
18 & 9.10878780157116 \tabularnewline
19 & 9.20244890347828 \tabularnewline
20 & 9.22074667891295 \tabularnewline
21 & 9.55981171362701 \tabularnewline
22 & 9.93931587182941 \tabularnewline
23 & 10.6886076472774 \tabularnewline
24 & 10.9219961545498 \tabularnewline
25 & 11.0968463988649 \tabularnewline
26 & 11.1022520238013 \tabularnewline
27 & 11.5387679774247 \tabularnewline
28 & 11.9812353286295 \tabularnewline
29 & 12.1485238810851 \tabularnewline
30 & 12.4630199539865 \tabularnewline
31 & 12.5159897730863 \tabularnewline
32 & 12.6933732419447 \tabularnewline
33 & 12.7232071428551 \tabularnewline
34 & 12.9327782434657 \tabularnewline
35 & 13.2778010227598 \tabularnewline
36 & 13.8706261456448 \tabularnewline
37 & 16.1877658136178 \tabularnewline
38 & 16.4432444264393 \tabularnewline
39 & 16.4556563508604 \tabularnewline
40 & 16.8257176018251 \tabularnewline
41 & 17.3246036494697 \tabularnewline
42 & 18.0926901504162 \tabularnewline
43 & 18.5460971915411 \tabularnewline
44 & 19.2980988184615 \tabularnewline
45 & 19.7264910609359 \tabularnewline
46 & 19.8626044828014 \tabularnewline
47 & 20.5783867200517 \tabularnewline
48 & 21.1548365802976 \tabularnewline
49 & 22.0460266334611 \tabularnewline
50 & 25.3856489850655 \tabularnewline
51 & 25.9538630751251 \tabularnewline
52 & 26.1483676792489 \tabularnewline
53 & 28.0010737240974 \tabularnewline
54 & 30.0519525358814 \tabularnewline
55 & 31.3894886865014 \tabularnewline
56 & 34.4427361073134 \tabularnewline
57 & 35.7677815929308 \tabularnewline
58 & 35.8075805043027 \tabularnewline
59 & 36.1443808091085 \tabularnewline
60 & 42.5006787151671 \tabularnewline
61 & 43.438866683393 \tabularnewline
62 & 44.847311681285 \tabularnewline
63 & 51.1426642805709 \tabularnewline
64 & 59.5282204812653 \tabularnewline
65 & 66.7711550432266 \tabularnewline
66 & 80.8024093157599 \tabularnewline
67 & 92.4473793897082 \tabularnewline
68 & 115.345813332353 \tabularnewline
69 & 149.596098950422 \tabularnewline
70 & 212.144261567956 \tabularnewline
71 & 219.046075446177 \tabularnewline
72 & 661.482319874866 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24448&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]3.55949434611153[/C][/ROW]
[ROW][C]2[/C][C]5.22589705218157[/C][/ROW]
[ROW][C]3[/C][C]5.85385019978483[/C][/ROW]
[ROW][C]4[/C][C]6.01581249707803[/C][/ROW]
[ROW][C]5[/C][C]6.43972049082879[/C][/ROW]
[ROW][C]6[/C][C]6.53222779762003[/C][/ROW]
[ROW][C]7[/C][C]7.29040465269247[/C][/ROW]
[ROW][C]8[/C][C]7.42293742395827[/C][/ROW]
[ROW][C]9[/C][C]7.7051930540383[/C][/ROW]
[ROW][C]10[/C][C]7.75112895003045[/C][/ROW]
[ROW][C]11[/C][C]7.97370679169983[/C][/ROW]
[ROW][C]12[/C][C]8.001249902359[/C][/ROW]
[ROW][C]13[/C][C]8.37675354776538[/C][/ROW]
[ROW][C]14[/C][C]8.43445315358381[/C][/ROW]
[ROW][C]15[/C][C]8.50058821494137[/C][/ROW]
[ROW][C]16[/C][C]8.70804225988828[/C][/ROW]
[ROW][C]17[/C][C]8.75328509760764[/C][/ROW]
[ROW][C]18[/C][C]9.10878780157116[/C][/ROW]
[ROW][C]19[/C][C]9.20244890347828[/C][/ROW]
[ROW][C]20[/C][C]9.22074667891295[/C][/ROW]
[ROW][C]21[/C][C]9.55981171362701[/C][/ROW]
[ROW][C]22[/C][C]9.93931587182941[/C][/ROW]
[ROW][C]23[/C][C]10.6886076472774[/C][/ROW]
[ROW][C]24[/C][C]10.9219961545498[/C][/ROW]
[ROW][C]25[/C][C]11.0968463988649[/C][/ROW]
[ROW][C]26[/C][C]11.1022520238013[/C][/ROW]
[ROW][C]27[/C][C]11.5387679774247[/C][/ROW]
[ROW][C]28[/C][C]11.9812353286295[/C][/ROW]
[ROW][C]29[/C][C]12.1485238810851[/C][/ROW]
[ROW][C]30[/C][C]12.4630199539865[/C][/ROW]
[ROW][C]31[/C][C]12.5159897730863[/C][/ROW]
[ROW][C]32[/C][C]12.6933732419447[/C][/ROW]
[ROW][C]33[/C][C]12.7232071428551[/C][/ROW]
[ROW][C]34[/C][C]12.9327782434657[/C][/ROW]
[ROW][C]35[/C][C]13.2778010227598[/C][/ROW]
[ROW][C]36[/C][C]13.8706261456448[/C][/ROW]
[ROW][C]37[/C][C]16.1877658136178[/C][/ROW]
[ROW][C]38[/C][C]16.4432444264393[/C][/ROW]
[ROW][C]39[/C][C]16.4556563508604[/C][/ROW]
[ROW][C]40[/C][C]16.8257176018251[/C][/ROW]
[ROW][C]41[/C][C]17.3246036494697[/C][/ROW]
[ROW][C]42[/C][C]18.0926901504162[/C][/ROW]
[ROW][C]43[/C][C]18.5460971915411[/C][/ROW]
[ROW][C]44[/C][C]19.2980988184615[/C][/ROW]
[ROW][C]45[/C][C]19.7264910609359[/C][/ROW]
[ROW][C]46[/C][C]19.8626044828014[/C][/ROW]
[ROW][C]47[/C][C]20.5783867200517[/C][/ROW]
[ROW][C]48[/C][C]21.1548365802976[/C][/ROW]
[ROW][C]49[/C][C]22.0460266334611[/C][/ROW]
[ROW][C]50[/C][C]25.3856489850655[/C][/ROW]
[ROW][C]51[/C][C]25.9538630751251[/C][/ROW]
[ROW][C]52[/C][C]26.1483676792489[/C][/ROW]
[ROW][C]53[/C][C]28.0010737240974[/C][/ROW]
[ROW][C]54[/C][C]30.0519525358814[/C][/ROW]
[ROW][C]55[/C][C]31.3894886865014[/C][/ROW]
[ROW][C]56[/C][C]34.4427361073134[/C][/ROW]
[ROW][C]57[/C][C]35.7677815929308[/C][/ROW]
[ROW][C]58[/C][C]35.8075805043027[/C][/ROW]
[ROW][C]59[/C][C]36.1443808091085[/C][/ROW]
[ROW][C]60[/C][C]42.5006787151671[/C][/ROW]
[ROW][C]61[/C][C]43.438866683393[/C][/ROW]
[ROW][C]62[/C][C]44.847311681285[/C][/ROW]
[ROW][C]63[/C][C]51.1426642805709[/C][/ROW]
[ROW][C]64[/C][C]59.5282204812653[/C][/ROW]
[ROW][C]65[/C][C]66.7711550432266[/C][/ROW]
[ROW][C]66[/C][C]80.8024093157599[/C][/ROW]
[ROW][C]67[/C][C]92.4473793897082[/C][/ROW]
[ROW][C]68[/C][C]115.345813332353[/C][/ROW]
[ROW][C]69[/C][C]149.596098950422[/C][/ROW]
[ROW][C]70[/C][C]212.144261567956[/C][/ROW]
[ROW][C]71[/C][C]219.046075446177[/C][/ROW]
[ROW][C]72[/C][C]661.482319874866[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24448&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24448&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of Dendrogram
LabelHeight
13.55949434611153
25.22589705218157
35.85385019978483
46.01581249707803
56.43972049082879
66.53222779762003
77.29040465269247
87.42293742395827
97.7051930540383
107.75112895003045
117.97370679169983
128.001249902359
138.37675354776538
148.43445315358381
158.50058821494137
168.70804225988828
178.75328509760764
189.10878780157116
199.20244890347828
209.22074667891295
219.55981171362701
229.93931587182941
2310.6886076472774
2410.9219961545498
2511.0968463988649
2611.1022520238013
2711.5387679774247
2811.9812353286295
2912.1485238810851
3012.4630199539865
3112.5159897730863
3212.6933732419447
3312.7232071428551
3412.9327782434657
3513.2778010227598
3613.8706261456448
3716.1877658136178
3816.4432444264393
3916.4556563508604
4016.8257176018251
4117.3246036494697
4218.0926901504162
4318.5460971915411
4419.2980988184615
4519.7264910609359
4619.8626044828014
4720.5783867200517
4821.1548365802976
4922.0460266334611
5025.3856489850655
5125.9538630751251
5226.1483676792489
5328.0010737240974
5430.0519525358814
5531.3894886865014
5634.4427361073134
5735.7677815929308
5835.8075805043027
5936.1443808091085
6042.5006787151671
6143.438866683393
6244.847311681285
6351.1426642805709
6459.5282204812653
6566.7711550432266
6680.8024093157599
6792.4473793897082
68115.345813332353
69149.596098950422
70212.144261567956
71219.046075446177
72661.482319874866



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')
}