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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 computationTue, 30 Oct 2007 07:51:35 -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/Oct/30/5yie1qtqk08cxuh1193755884.htm/, Retrieved Sun, 05 May 2024 04:22:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2157, Retrieved Sun, 05 May 2024 04:22:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ2
Estimated Impact336

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] [Workshop 4] [2007-10-30 14:51:35] [676e67eebaa0fa2a5b563d138d4b447b] [Current]
F    D    [Hierarchical Clustering] [q2 eigen tijdreek...] [2008-11-11 19:26:13] [e43247bc0ab243a5af99ac7f55ba0b41]
F RMPD    [Box-Cox Linearity Plot] [q3] [2008-11-11 19:29:26] [e43247bc0ab243a5af99ac7f55ba0b41]
Feedback Forum
2008-11-15 15:40:23 [Philip Van Herck] [reply] 
Deze dendogram geeft dan weer welke waarnemingen samengenomen kunnen worden. De waarnemingen in de verschillende ondervedelingen (takken) hebben een zeker verband. Op het einde van de dendogram kunnen we aflezen welke waarnemingen (aan de hand van rangnummer dat overeenkomt met de periodes) uit welke tak voorkomt. We kunnen zo ook zien dat bepaalde periodieke fenomenen naar voren komen.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103,1	119,5	98,6	98,1	98,6
100,6	125	98	101,1	98
103,1	145	106,8	111,1	106,8
95,5	105,3	96,6	93,3	96,7
90,5	116,9	100,1	100	100,2
90,9	120,1	107,7	108	107,7
88,8	88,9	91,5	70,4	92
90,7	78,4	97,8	75,4	98,4
94,3	114,6	107,4	105,5	107,4
104,6	113,3	117,5	112,3	117,7
111,1	117	105,6	102,5	105,7
110,8	99,6	97,4	93,5	97,5
107,2	99,4	99,5	86,7	99,9
99	101,9	98	95,2	98,2
99	115,2	104,3	103,8	104,5
91	108,5	100,6	97	100,8
96,2	113,8	101,1	95,5	101,5
96,9	121	103,9	101	103,9
96,2	92,2	96,9	67,5	99,6
100,1	90,2	95,5	64	98,4
99	101,5	108,4	106,7	112,7
115,4	126,6	117	100,6	118,4
106,9	93,9	103,8	101,2	108,1
107,1	89,8	100,8	93,1	105,4
99,3	93,4	110,6	84,2	114,6
99,2	101,5	104	85,8	106,9
108,3	110,4	112,6	91,8	115,9
105,6	105,9	107,3	92,4	109,8
99,5	108,4	98,9	80,3	101,8
107,4	113,9	109,8	79,7	114,2
93,1	86,1	104,9	62,5	110,8
88,1	69,4	102,2	57,1	108,4
110,7	101,2	123,9	100,8	127,5
113,1	100,5	124,9	100,7	128,6
99,6	98	112,7	86,2	116,6
93,6	106,6	121,9	83,2	127,4
98,6	90,1	100,6	71,7	105
99,6	96,9	104,3	77,5	108,3
114,3	125,9	120,4	89,8	125
107,8	112	107,5	80,3	111,6
101,2	100	102,9	78,7	106,5
112,5	123,9	125,6	93,8	130,3
100,5	79,8	107,5	57,6	115
93,9	83,4	108,8	60,6	116,1
116,2	113,6	128,4	91	134
112	112,9	121,1	85,3	126,5
106,4	104	119,5	77,4	125,8
95,7	109,9	128,7	77,3	136,4
96	99	108,7	68,3	114,9
95,8	106,3	105,5	69,9	110,9
103	128,9	119,8	81,7	125,5
102,2	111,1	111,3	75,1	116,8
98,4	102,9	110,6	69,9	116,8
111,4	130	120,1	84	125,5
86,6	87	97,5	54,3	104,2
91,3	87,5	107,7	60	115,1
107,9	117,6	127,3	89,9	132,8
101,8	103,4	117,2	77	123,3
104,4	110,8	119,8	85,3	124,8
93,4	112,6	116,2	77,6	122
100,1	102,5	111	69,2	117,4
98,5	112,4	112,4	75,5	117,9
112,9	135,6	130,6	85,7	137,4
101,4	105,1	109,1	72,2	114,6
107,1	127,7	118,8	79,9	124,7
110,8	137	123,9	85,3	129,6
90,3	91	101,6	52,2	109,4
95,5	90,5	112,8	61,2	120,9
111,4	122,4	128	82,4	134,9
113	123,3	129,6	85,4	136,3
107,5	124,3	125,8	78,2	133,2
95,9	120	119,5	70,2	127,2
106,3	118,1	115,7	70,2	122,7
105,2	119	113,6	69,3	120,5
117,2	142,7	129,7	77,5	137,8
106,9	123,6	112	66,1	119,1
108,2	129,6	116,8	69	124,3
110	146,9	126,3	75,3	134,3
96,1	108,7	112,9	58,2	121,7
100,6	99,4	115,9	59,7	125

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2157&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]2 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=2157&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2157&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Summary of Dendrogram
LabelHeight
12.01494416796098
22.91032644217104
33.47562943939656
44.02243707222376
54.1097445176069
64.23792402008343
74.33704968844028
84.80936586256441
95.11272921246568
105.62405547625554
115.76367938039583
125.80172388174411
135.9042357676502
146.32596452273507
156.58483105326174
166.79852925271341
177.33038838043221
187.62364742101837
197.69415362466853
208.1700673191841
218.33126641033642
228.4279338567296
238.7322303358929
248.7574701893959
258.81375615968757
268.8289297199604
279.23038460737146
289.65401470891774
299.90605875209713
309.9373034571759
319.96235270609868
3210.0362830165079
3310.5952819688765
3410.6720754870332
3511.1648267830396
3611.2697310375211
3711.3454852310461
3811.3525327570547
3911.3600176056202
4013.1196573819491
4113.8344619181306
4213.8797500466067
4314.7194578827144
4414.7777774853826
4514.8158698698389
4616.9705467748593
4717.1213413430579
4817.6002840886163
4918.2058264652671
5018.3160170652479
5119.0482803284852
5219.3977587922622
5320.9384011764675
5421.1686702506837
5521.9437245504921
5623.7207805989398
5724.5576451045647
5826.33021040626
5926.6672453218299
6027.9576274179053
6130.7874722569039
6231.366758381802
6333.9921417448659
6435.5514545111563
6538.4019165246154
6641.4396358205299
6743.2794755411843
6844.9382934981699
6947.2531912951542
7053.5605310710833
7161.6585340373616
7263.1744337945558
7375.1001956940621
7482.5255657715052
7596.733540820164
76152.366124224885
77264.639154774481
78432.352008298797
79515.971804059776

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 2.01494416796098 \tabularnewline
2 & 2.91032644217104 \tabularnewline
3 & 3.47562943939656 \tabularnewline
4 & 4.02243707222376 \tabularnewline
5 & 4.1097445176069 \tabularnewline
6 & 4.23792402008343 \tabularnewline
7 & 4.33704968844028 \tabularnewline
8 & 4.80936586256441 \tabularnewline
9 & 5.11272921246568 \tabularnewline
10 & 5.62405547625554 \tabularnewline
11 & 5.76367938039583 \tabularnewline
12 & 5.80172388174411 \tabularnewline
13 & 5.9042357676502 \tabularnewline
14 & 6.32596452273507 \tabularnewline
15 & 6.58483105326174 \tabularnewline
16 & 6.79852925271341 \tabularnewline
17 & 7.33038838043221 \tabularnewline
18 & 7.62364742101837 \tabularnewline
19 & 7.69415362466853 \tabularnewline
20 & 8.1700673191841 \tabularnewline
21 & 8.33126641033642 \tabularnewline
22 & 8.4279338567296 \tabularnewline
23 & 8.7322303358929 \tabularnewline
24 & 8.7574701893959 \tabularnewline
25 & 8.81375615968757 \tabularnewline
26 & 8.8289297199604 \tabularnewline
27 & 9.23038460737146 \tabularnewline
28 & 9.65401470891774 \tabularnewline
29 & 9.90605875209713 \tabularnewline
30 & 9.9373034571759 \tabularnewline
31 & 9.96235270609868 \tabularnewline
32 & 10.0362830165079 \tabularnewline
33 & 10.5952819688765 \tabularnewline
34 & 10.6720754870332 \tabularnewline
35 & 11.1648267830396 \tabularnewline
36 & 11.2697310375211 \tabularnewline
37 & 11.3454852310461 \tabularnewline
38 & 11.3525327570547 \tabularnewline
39 & 11.3600176056202 \tabularnewline
40 & 13.1196573819491 \tabularnewline
41 & 13.8344619181306 \tabularnewline
42 & 13.8797500466067 \tabularnewline
43 & 14.7194578827144 \tabularnewline
44 & 14.7777774853826 \tabularnewline
45 & 14.8158698698389 \tabularnewline
46 & 16.9705467748593 \tabularnewline
47 & 17.1213413430579 \tabularnewline
48 & 17.6002840886163 \tabularnewline
49 & 18.2058264652671 \tabularnewline
50 & 18.3160170652479 \tabularnewline
51 & 19.0482803284852 \tabularnewline
52 & 19.3977587922622 \tabularnewline
53 & 20.9384011764675 \tabularnewline
54 & 21.1686702506837 \tabularnewline
55 & 21.9437245504921 \tabularnewline
56 & 23.7207805989398 \tabularnewline
57 & 24.5576451045647 \tabularnewline
58 & 26.33021040626 \tabularnewline
59 & 26.6672453218299 \tabularnewline
60 & 27.9576274179053 \tabularnewline
61 & 30.7874722569039 \tabularnewline
62 & 31.366758381802 \tabularnewline
63 & 33.9921417448659 \tabularnewline
64 & 35.5514545111563 \tabularnewline
65 & 38.4019165246154 \tabularnewline
66 & 41.4396358205299 \tabularnewline
67 & 43.2794755411843 \tabularnewline
68 & 44.9382934981699 \tabularnewline
69 & 47.2531912951542 \tabularnewline
70 & 53.5605310710833 \tabularnewline
71 & 61.6585340373616 \tabularnewline
72 & 63.1744337945558 \tabularnewline
73 & 75.1001956940621 \tabularnewline
74 & 82.5255657715052 \tabularnewline
75 & 96.733540820164 \tabularnewline
76 & 152.366124224885 \tabularnewline
77 & 264.639154774481 \tabularnewline
78 & 432.352008298797 \tabularnewline
79 & 515.971804059776 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2157&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]2.01494416796098[/C][/ROW]
[ROW][C]2[/C][C]2.91032644217104[/C][/ROW]
[ROW][C]3[/C][C]3.47562943939656[/C][/ROW]
[ROW][C]4[/C][C]4.02243707222376[/C][/ROW]
[ROW][C]5[/C][C]4.1097445176069[/C][/ROW]
[ROW][C]6[/C][C]4.23792402008343[/C][/ROW]
[ROW][C]7[/C][C]4.33704968844028[/C][/ROW]
[ROW][C]8[/C][C]4.80936586256441[/C][/ROW]
[ROW][C]9[/C][C]5.11272921246568[/C][/ROW]
[ROW][C]10[/C][C]5.62405547625554[/C][/ROW]
[ROW][C]11[/C][C]5.76367938039583[/C][/ROW]
[ROW][C]12[/C][C]5.80172388174411[/C][/ROW]
[ROW][C]13[/C][C]5.9042357676502[/C][/ROW]
[ROW][C]14[/C][C]6.32596452273507[/C][/ROW]
[ROW][C]15[/C][C]6.58483105326174[/C][/ROW]
[ROW][C]16[/C][C]6.79852925271341[/C][/ROW]
[ROW][C]17[/C][C]7.33038838043221[/C][/ROW]
[ROW][C]18[/C][C]7.62364742101837[/C][/ROW]
[ROW][C]19[/C][C]7.69415362466853[/C][/ROW]
[ROW][C]20[/C][C]8.1700673191841[/C][/ROW]
[ROW][C]21[/C][C]8.33126641033642[/C][/ROW]
[ROW][C]22[/C][C]8.4279338567296[/C][/ROW]
[ROW][C]23[/C][C]8.7322303358929[/C][/ROW]
[ROW][C]24[/C][C]8.7574701893959[/C][/ROW]
[ROW][C]25[/C][C]8.81375615968757[/C][/ROW]
[ROW][C]26[/C][C]8.8289297199604[/C][/ROW]
[ROW][C]27[/C][C]9.23038460737146[/C][/ROW]
[ROW][C]28[/C][C]9.65401470891774[/C][/ROW]
[ROW][C]29[/C][C]9.90605875209713[/C][/ROW]
[ROW][C]30[/C][C]9.9373034571759[/C][/ROW]
[ROW][C]31[/C][C]9.96235270609868[/C][/ROW]
[ROW][C]32[/C][C]10.0362830165079[/C][/ROW]
[ROW][C]33[/C][C]10.5952819688765[/C][/ROW]
[ROW][C]34[/C][C]10.6720754870332[/C][/ROW]
[ROW][C]35[/C][C]11.1648267830396[/C][/ROW]
[ROW][C]36[/C][C]11.2697310375211[/C][/ROW]
[ROW][C]37[/C][C]11.3454852310461[/C][/ROW]
[ROW][C]38[/C][C]11.3525327570547[/C][/ROW]
[ROW][C]39[/C][C]11.3600176056202[/C][/ROW]
[ROW][C]40[/C][C]13.1196573819491[/C][/ROW]
[ROW][C]41[/C][C]13.8344619181306[/C][/ROW]
[ROW][C]42[/C][C]13.8797500466067[/C][/ROW]
[ROW][C]43[/C][C]14.7194578827144[/C][/ROW]
[ROW][C]44[/C][C]14.7777774853826[/C][/ROW]
[ROW][C]45[/C][C]14.8158698698389[/C][/ROW]
[ROW][C]46[/C][C]16.9705467748593[/C][/ROW]
[ROW][C]47[/C][C]17.1213413430579[/C][/ROW]
[ROW][C]48[/C][C]17.6002840886163[/C][/ROW]
[ROW][C]49[/C][C]18.2058264652671[/C][/ROW]
[ROW][C]50[/C][C]18.3160170652479[/C][/ROW]
[ROW][C]51[/C][C]19.0482803284852[/C][/ROW]
[ROW][C]52[/C][C]19.3977587922622[/C][/ROW]
[ROW][C]53[/C][C]20.9384011764675[/C][/ROW]
[ROW][C]54[/C][C]21.1686702506837[/C][/ROW]
[ROW][C]55[/C][C]21.9437245504921[/C][/ROW]
[ROW][C]56[/C][C]23.7207805989398[/C][/ROW]
[ROW][C]57[/C][C]24.5576451045647[/C][/ROW]
[ROW][C]58[/C][C]26.33021040626[/C][/ROW]
[ROW][C]59[/C][C]26.6672453218299[/C][/ROW]
[ROW][C]60[/C][C]27.9576274179053[/C][/ROW]
[ROW][C]61[/C][C]30.7874722569039[/C][/ROW]
[ROW][C]62[/C][C]31.366758381802[/C][/ROW]
[ROW][C]63[/C][C]33.9921417448659[/C][/ROW]
[ROW][C]64[/C][C]35.5514545111563[/C][/ROW]
[ROW][C]65[/C][C]38.4019165246154[/C][/ROW]
[ROW][C]66[/C][C]41.4396358205299[/C][/ROW]
[ROW][C]67[/C][C]43.2794755411843[/C][/ROW]
[ROW][C]68[/C][C]44.9382934981699[/C][/ROW]
[ROW][C]69[/C][C]47.2531912951542[/C][/ROW]
[ROW][C]70[/C][C]53.5605310710833[/C][/ROW]
[ROW][C]71[/C][C]61.6585340373616[/C][/ROW]
[ROW][C]72[/C][C]63.1744337945558[/C][/ROW]
[ROW][C]73[/C][C]75.1001956940621[/C][/ROW]
[ROW][C]74[/C][C]82.5255657715052[/C][/ROW]
[ROW][C]75[/C][C]96.733540820164[/C][/ROW]
[ROW][C]76[/C][C]152.366124224885[/C][/ROW]
[ROW][C]77[/C][C]264.639154774481[/C][/ROW]
[ROW][C]78[/C][C]432.352008298797[/C][/ROW]
[ROW][C]79[/C][C]515.971804059776[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2157&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2157&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
12.01494416796098
22.91032644217104
33.47562943939656
44.02243707222376
54.1097445176069
64.23792402008343
74.33704968844028
84.80936586256441
95.11272921246568
105.62405547625554
115.76367938039583
125.80172388174411
135.9042357676502
146.32596452273507
156.58483105326174
166.79852925271341
177.33038838043221
187.62364742101837
197.69415362466853
208.1700673191841
218.33126641033642
228.4279338567296
238.7322303358929
248.7574701893959
258.81375615968757
268.8289297199604
279.23038460737146
289.65401470891774
299.90605875209713
309.9373034571759
319.96235270609868
3210.0362830165079
3310.5952819688765
3410.6720754870332
3511.1648267830396
3611.2697310375211
3711.3454852310461
3811.3525327570547
3911.3600176056202
4013.1196573819491
4113.8344619181306
4213.8797500466067
4314.7194578827144
4414.7777774853826
4514.8158698698389
4616.9705467748593
4717.1213413430579
4817.6002840886163
4918.2058264652671
5018.3160170652479
5119.0482803284852
5219.3977587922622
5320.9384011764675
5421.1686702506837
5521.9437245504921
5623.7207805989398
5724.5576451045647
5826.33021040626
5926.6672453218299
6027.9576274179053
6130.7874722569039
6231.366758381802
6333.9921417448659
6435.5514545111563
6538.4019165246154
6641.4396358205299
6743.2794755411843
6844.9382934981699
6947.2531912951542
7053.5605310710833
7161.6585340373616
7263.1744337945558
7375.1001956940621
7482.5255657715052
7596.733540820164
76152.366124224885
77264.639154774481
78432.352008298797
79515.971804059776


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')
}