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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 14:30:22 -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/t1226266261h33owysb43r5zfu.htm/, Retrieved Tue, 14 May 2024 21:46:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22882, Retrieved Tue, 14 May 2024 21:46:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact214

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Testing Population Proportion - Critical Value] [vraag 1] [2008-11-09 20:15:31] [c45c87b96bbf32ffc2144fc37d767b2e]
- RM    [Minimum Sample Size - Testing Proportions] [vraag 4] [2008-11-09 20:51:51] [c45c87b96bbf32ffc2144fc37d767b2e]
F RM D      [Hierarchical Clustering] [vraag 2] [2008-11-09 21:30:22] [3dc594a6c62226e1e98766c4d385bfaa] [Current]
-   PD        [Hierarchical Clustering] [dendrogram] [2008-12-21 14:09:41] [c45c87b96bbf32ffc2144fc37d767b2e]
- RMPD          [Histogram] [Histogram groep 1] [2008-12-21 16:48:39] [c45c87b96bbf32ffc2144fc37d767b2e]
-  M D          [Hierarchical Clustering] [] [2009-12-30 13:17:52] [d2d412c7f4d35ffbf5ee5ee89db327d4]
-   PD            [Hierarchical Clustering] [] [2009-12-30 14:13:32] [d2d412c7f4d35ffbf5ee5ee89db327d4]
Feedback Forum
2008-11-24 20:34:01 [Michaël De Kuyer] [reply] 
Om tijdreeksen in clusters op te delen wordt gebruik gemaakt van een dendogram, ook boomstructuur genoemd.
De bedoeling hiervan is om inzicht te krijgen in welke observaties van de tijdreeks gelijkaardig zijn. De puntjes in het dendrogram zijn observaties waar clusters van gemaakt worden. Deze methode wordt meestal gebruikt voor niet- tijdreeksen maar eerder in de marketing sector om bijvoorbeeld te zien welke producten samen horen.

Aan de hand van mijn dendrogram kan ik niet echt clusters vormen aangezien er zeer veel deeltakken zijn.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2293	4348	440427	1.90
2045	3603	386715	1.76
1532	2700	291787	1.76
1333	2640	278253	1.98
1583	2916	300903	1.84
1712	3180	327695	1.86
2641	4151	471590	1.57
2267	4023	442850	1.77
2126	3431	387181	1.61
2231	3874	420099	1.74
1517	2617	289850	1.73
2010	3580	392468	1.78
2628	5267	549174	2.00
2115	3832	415506	1.81
1829	3441	356662	1.88
1636	3228	338612	1.97
1787	3397	359886	1.90
2122	3971	410547	1.87
2620	4625	495272	1.77
2555	4486	474588	1.76
2337	4131	442893	1.77
2524	4686	477793	1.86
1801	3174	336263	1.76
2417	4282	449838	1.77
2389	4209	451406	1.76
2266	4158	439690	1.83
2135	3936	401513	1.84
1755	3149	326472	1.79
1907	3623	369464	1.90
2178	4230	429525	1.94
2345	4443	464658	1.89
2674	4810	510691	1.80
2765	4853	513151	1.76
2786	5050	538609	1.81
2004	3553	398949	1.77
2589	4674	511635	1.81
2739	5412	554318	1.98
2700	5131	515879	1.90
2459	4856	488122	1.97
1965	3980	401716	2.03
2152	4431	453358	2.06
2379	4606	464884	1.94
2930	5352	571868	1.83
2691	4640	497485	1.72
2852	5170	538214	1.81
2752	4824	502396	1.75
1787	3280	349385	1.84
2580	4706	502427	1.82
2604	4909	514106	1.89
2532	5092	527537	2.01
2265	4911	495918	2.17
1745	3824	376847	2.19
1914	4214	420552	2.20
2148	4449	442679	2.07
2466	4486	478422	1.82
2498	4777	483796	1.91
2512	5132	529032	2.04
2458	4522	482991	1.84
1825	3295	354287	1.81
2267	4281	459146	1.89
2364	4590	473744	1.94
2328	4623	478642	1.99
2034	4075	426208	2.00
1587	3398	348908	2.14
1633	3029	321310	1.85

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22882&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]4 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=22882&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22882&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 time4 seconds
R Server'George Udny Yule' @ 72.249.76.132






Summary of Dendrogram
LabelHeight
1135.694509837355
2210.876752867641
3268.412063998621
4280.715162575875
5293.620552584454
6418.068176258371
7427.365288716807
8503.290197103023
9530.521526424706
10649.074889053644
11662.574525317719
12761.576000737943
13790.65615788407
14845.36974449054
15871.569292942334
16957.526500990965
17970.093818607252
181224.14827733408
191495.66874704929
201536.64342073885
211569.9480883456
221646.33113391565
231789.42141489924
241938.83547545943
251978.82720064183
262215.66381405212
272258.92231581788
282355.40698056620
292379.48671038525
302595.75538233093
313211.38381542911
323224.57377034547
333323.74036344598
344326.89704102143
354352.11466100102
364594.65657094195
374902.17023377402
384914.82431027804
394960.95263065472
405147.24023146385
415164.83571893628
425290.37106722203
435514.93173121844
445658.980212017
455791.08530665021
466481.05901840895
476726.52251441263
486947.10198572038
497155.5420507464
507387.5120361391
518265.18892708449
528568.46433207258
538832.4000716453
549118.70127849356
559188.37134931431
569581.4174316747
579875.03241437212
5810165.6358882315
5910297.5199455451
6010568.4094373799
6111598.4824034224
6211659.2756641268
6317551.1418723256
6420407.3741083977

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 135.694509837355 \tabularnewline
2 & 210.876752867641 \tabularnewline
3 & 268.412063998621 \tabularnewline
4 & 280.715162575875 \tabularnewline
5 & 293.620552584454 \tabularnewline
6 & 418.068176258371 \tabularnewline
7 & 427.365288716807 \tabularnewline
8 & 503.290197103023 \tabularnewline
9 & 530.521526424706 \tabularnewline
10 & 649.074889053644 \tabularnewline
11 & 662.574525317719 \tabularnewline
12 & 761.576000737943 \tabularnewline
13 & 790.65615788407 \tabularnewline
14 & 845.36974449054 \tabularnewline
15 & 871.569292942334 \tabularnewline
16 & 957.526500990965 \tabularnewline
17 & 970.093818607252 \tabularnewline
18 & 1224.14827733408 \tabularnewline
19 & 1495.66874704929 \tabularnewline
20 & 1536.64342073885 \tabularnewline
21 & 1569.9480883456 \tabularnewline
22 & 1646.33113391565 \tabularnewline
23 & 1789.42141489924 \tabularnewline
24 & 1938.83547545943 \tabularnewline
25 & 1978.82720064183 \tabularnewline
26 & 2215.66381405212 \tabularnewline
27 & 2258.92231581788 \tabularnewline
28 & 2355.40698056620 \tabularnewline
29 & 2379.48671038525 \tabularnewline
30 & 2595.75538233093 \tabularnewline
31 & 3211.38381542911 \tabularnewline
32 & 3224.57377034547 \tabularnewline
33 & 3323.74036344598 \tabularnewline
34 & 4326.89704102143 \tabularnewline
35 & 4352.11466100102 \tabularnewline
36 & 4594.65657094195 \tabularnewline
37 & 4902.17023377402 \tabularnewline
38 & 4914.82431027804 \tabularnewline
39 & 4960.95263065472 \tabularnewline
40 & 5147.24023146385 \tabularnewline
41 & 5164.83571893628 \tabularnewline
42 & 5290.37106722203 \tabularnewline
43 & 5514.93173121844 \tabularnewline
44 & 5658.980212017 \tabularnewline
45 & 5791.08530665021 \tabularnewline
46 & 6481.05901840895 \tabularnewline
47 & 6726.52251441263 \tabularnewline
48 & 6947.10198572038 \tabularnewline
49 & 7155.5420507464 \tabularnewline
50 & 7387.5120361391 \tabularnewline
51 & 8265.18892708449 \tabularnewline
52 & 8568.46433207258 \tabularnewline
53 & 8832.4000716453 \tabularnewline
54 & 9118.70127849356 \tabularnewline
55 & 9188.37134931431 \tabularnewline
56 & 9581.4174316747 \tabularnewline
57 & 9875.03241437212 \tabularnewline
58 & 10165.6358882315 \tabularnewline
59 & 10297.5199455451 \tabularnewline
60 & 10568.4094373799 \tabularnewline
61 & 11598.4824034224 \tabularnewline
62 & 11659.2756641268 \tabularnewline
63 & 17551.1418723256 \tabularnewline
64 & 20407.3741083977 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22882&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]135.694509837355[/C][/ROW]
[ROW][C]2[/C][C]210.876752867641[/C][/ROW]
[ROW][C]3[/C][C]268.412063998621[/C][/ROW]
[ROW][C]4[/C][C]280.715162575875[/C][/ROW]
[ROW][C]5[/C][C]293.620552584454[/C][/ROW]
[ROW][C]6[/C][C]418.068176258371[/C][/ROW]
[ROW][C]7[/C][C]427.365288716807[/C][/ROW]
[ROW][C]8[/C][C]503.290197103023[/C][/ROW]
[ROW][C]9[/C][C]530.521526424706[/C][/ROW]
[ROW][C]10[/C][C]649.074889053644[/C][/ROW]
[ROW][C]11[/C][C]662.574525317719[/C][/ROW]
[ROW][C]12[/C][C]761.576000737943[/C][/ROW]
[ROW][C]13[/C][C]790.65615788407[/C][/ROW]
[ROW][C]14[/C][C]845.36974449054[/C][/ROW]
[ROW][C]15[/C][C]871.569292942334[/C][/ROW]
[ROW][C]16[/C][C]957.526500990965[/C][/ROW]
[ROW][C]17[/C][C]970.093818607252[/C][/ROW]
[ROW][C]18[/C][C]1224.14827733408[/C][/ROW]
[ROW][C]19[/C][C]1495.66874704929[/C][/ROW]
[ROW][C]20[/C][C]1536.64342073885[/C][/ROW]
[ROW][C]21[/C][C]1569.9480883456[/C][/ROW]
[ROW][C]22[/C][C]1646.33113391565[/C][/ROW]
[ROW][C]23[/C][C]1789.42141489924[/C][/ROW]
[ROW][C]24[/C][C]1938.83547545943[/C][/ROW]
[ROW][C]25[/C][C]1978.82720064183[/C][/ROW]
[ROW][C]26[/C][C]2215.66381405212[/C][/ROW]
[ROW][C]27[/C][C]2258.92231581788[/C][/ROW]
[ROW][C]28[/C][C]2355.40698056620[/C][/ROW]
[ROW][C]29[/C][C]2379.48671038525[/C][/ROW]
[ROW][C]30[/C][C]2595.75538233093[/C][/ROW]
[ROW][C]31[/C][C]3211.38381542911[/C][/ROW]
[ROW][C]32[/C][C]3224.57377034547[/C][/ROW]
[ROW][C]33[/C][C]3323.74036344598[/C][/ROW]
[ROW][C]34[/C][C]4326.89704102143[/C][/ROW]
[ROW][C]35[/C][C]4352.11466100102[/C][/ROW]
[ROW][C]36[/C][C]4594.65657094195[/C][/ROW]
[ROW][C]37[/C][C]4902.17023377402[/C][/ROW]
[ROW][C]38[/C][C]4914.82431027804[/C][/ROW]
[ROW][C]39[/C][C]4960.95263065472[/C][/ROW]
[ROW][C]40[/C][C]5147.24023146385[/C][/ROW]
[ROW][C]41[/C][C]5164.83571893628[/C][/ROW]
[ROW][C]42[/C][C]5290.37106722203[/C][/ROW]
[ROW][C]43[/C][C]5514.93173121844[/C][/ROW]
[ROW][C]44[/C][C]5658.980212017[/C][/ROW]
[ROW][C]45[/C][C]5791.08530665021[/C][/ROW]
[ROW][C]46[/C][C]6481.05901840895[/C][/ROW]
[ROW][C]47[/C][C]6726.52251441263[/C][/ROW]
[ROW][C]48[/C][C]6947.10198572038[/C][/ROW]
[ROW][C]49[/C][C]7155.5420507464[/C][/ROW]
[ROW][C]50[/C][C]7387.5120361391[/C][/ROW]
[ROW][C]51[/C][C]8265.18892708449[/C][/ROW]
[ROW][C]52[/C][C]8568.46433207258[/C][/ROW]
[ROW][C]53[/C][C]8832.4000716453[/C][/ROW]
[ROW][C]54[/C][C]9118.70127849356[/C][/ROW]
[ROW][C]55[/C][C]9188.37134931431[/C][/ROW]
[ROW][C]56[/C][C]9581.4174316747[/C][/ROW]
[ROW][C]57[/C][C]9875.03241437212[/C][/ROW]
[ROW][C]58[/C][C]10165.6358882315[/C][/ROW]
[ROW][C]59[/C][C]10297.5199455451[/C][/ROW]
[ROW][C]60[/C][C]10568.4094373799[/C][/ROW]
[ROW][C]61[/C][C]11598.4824034224[/C][/ROW]
[ROW][C]62[/C][C]11659.2756641268[/C][/ROW]
[ROW][C]63[/C][C]17551.1418723256[/C][/ROW]
[ROW][C]64[/C][C]20407.3741083977[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22882&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22882&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
1135.694509837355
2210.876752867641
3268.412063998621
4280.715162575875
5293.620552584454
6418.068176258371
7427.365288716807
8503.290197103023
9530.521526424706
10649.074889053644
11662.574525317719
12761.576000737943
13790.65615788407
14845.36974449054
15871.569292942334
16957.526500990965
17970.093818607252
181224.14827733408
191495.66874704929
201536.64342073885
211569.9480883456
221646.33113391565
231789.42141489924
241938.83547545943
251978.82720064183
262215.66381405212
272258.92231581788
282355.40698056620
292379.48671038525
302595.75538233093
313211.38381542911
323224.57377034547
333323.74036344598
344326.89704102143
354352.11466100102
364594.65657094195
374902.17023377402
384914.82431027804
394960.95263065472
405147.24023146385
415164.83571893628
425290.37106722203
435514.93173121844
445658.980212017
455791.08530665021
466481.05901840895
476726.52251441263
486947.10198572038
497155.5420507464
507387.5120361391
518265.18892708449
528568.46433207258
538832.4000716453
549118.70127849356
559188.37134931431
569581.4174316747
579875.03241437212
5810165.6358882315
5910297.5199455451
6010568.4094373799
6111598.4824034224
6211659.2756641268
6317551.1418723256
6420407.3741083977






Summary of Cut Dendrogram
LabelHeight
17387.5120361391
210087.9566196046
310131.3544033473
411941.4290520212
511948.5862065416
612278.7855240430
712566.9727780888
813337.1631459767
914393.6754347247
1015194.6284379464
1115508.0865118550
1215641.2373935120
1316388.9532094762
1419681.3886430517
1519846.3474958355
1620123.5136724579
1721303.0980922728
1821640.6804108885
1924257.1344029852

\begin{tabular}{lllllllll}
\hline
Summary of Cut Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 7387.5120361391 \tabularnewline
2 & 10087.9566196046 \tabularnewline
3 & 10131.3544033473 \tabularnewline
4 & 11941.4290520212 \tabularnewline
5 & 11948.5862065416 \tabularnewline
6 & 12278.7855240430 \tabularnewline
7 & 12566.9727780888 \tabularnewline
8 & 13337.1631459767 \tabularnewline
9 & 14393.6754347247 \tabularnewline
10 & 15194.6284379464 \tabularnewline
11 & 15508.0865118550 \tabularnewline
12 & 15641.2373935120 \tabularnewline
13 & 16388.9532094762 \tabularnewline
14 & 19681.3886430517 \tabularnewline
15 & 19846.3474958355 \tabularnewline
16 & 20123.5136724579 \tabularnewline
17 & 21303.0980922728 \tabularnewline
18 & 21640.6804108885 \tabularnewline
19 & 24257.1344029852 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22882&T=2

[TABLE]
[ROW][C]Summary of Cut Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]7387.5120361391[/C][/ROW]
[ROW][C]2[/C][C]10087.9566196046[/C][/ROW]
[ROW][C]3[/C][C]10131.3544033473[/C][/ROW]
[ROW][C]4[/C][C]11941.4290520212[/C][/ROW]
[ROW][C]5[/C][C]11948.5862065416[/C][/ROW]
[ROW][C]6[/C][C]12278.7855240430[/C][/ROW]
[ROW][C]7[/C][C]12566.9727780888[/C][/ROW]
[ROW][C]8[/C][C]13337.1631459767[/C][/ROW]
[ROW][C]9[/C][C]14393.6754347247[/C][/ROW]
[ROW][C]10[/C][C]15194.6284379464[/C][/ROW]
[ROW][C]11[/C][C]15508.0865118550[/C][/ROW]
[ROW][C]12[/C][C]15641.2373935120[/C][/ROW]
[ROW][C]13[/C][C]16388.9532094762[/C][/ROW]
[ROW][C]14[/C][C]19681.3886430517[/C][/ROW]
[ROW][C]15[/C][C]19846.3474958355[/C][/ROW]
[ROW][C]16[/C][C]20123.5136724579[/C][/ROW]
[ROW][C]17[/C][C]21303.0980922728[/C][/ROW]
[ROW][C]18[/C][C]21640.6804108885[/C][/ROW]
[ROW][C]19[/C][C]24257.1344029852[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22882&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22882&T=2

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 Cut Dendrogram
LabelHeight
17387.5120361391
210087.9566196046
310131.3544033473
411941.4290520212
511948.5862065416
612278.7855240430
712566.9727780888
813337.1631459767
914393.6754347247
1015194.6284379464
1115508.0865118550
1215641.2373935120
1316388.9532094762
1419681.3886430517
1519846.3474958355
1620123.5136724579
1721303.0980922728
1821640.6804108885
1924257.1344029852


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 98 ; par2 = 0.8571 ; par3 = 0.69 ; par4 = 0.05 ;
Parameters (R input):
par1 = single ; par2 = 20 ; par3 = FALSE ; par4 = TRUE ;
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')
}