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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_hierarchicalclustering.wasp

Title produced by software

Hierarchical Clustering

Date of computation

Tue, 11 Nov 2008 08:27:51 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/11/t1226417397ywvgqn0vdxs9te0.htm/, Retrieved Mon, 20 May 2024 07:28:36 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23598, Retrieved Mon, 20 May 2024 07:28:36 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

132

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Bivariate Kernel Density Estimation] [] [2008-11-11 15:01:49] [29747f79f5beb5b2516e1271770ecb47]
F RMPD  [Partial Correlation] [] [2008-11-11 15:17:50] [29747f79f5beb5b2516e1271770ecb47]
F RMPD    [Trivariate Scatterplots] [] [2008-11-11 15:21:20] [29747f79f5beb5b2516e1271770ecb47]
F RMPD        [Hierarchical Clustering] [] [2008-11-11 15:27:51] [c0a347e3519123f7eef62b705326dad9] [Current]

Feedback Forum

2008-11-24 17:54:24 [Jan Cavents] [reply] 
het dendrogram geeft de clusters weer. dit is louter een exploratieve methode, meestal gebruik in marketing. voor tijdreeksen is dit niet optimaal.

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

97,6	89,6	6,4	9,1
96,9	92,8	6,3	9,0
105,6	107,6	6,3	8,6
102,8	104,6	6,4	7,9
101,7	103,0	6,3	7,7
104,2	106,9	6,0	7,8
92,7	56,3	6,2	9,1
91,9	93,4	6,3	9,4
106,5	109,1	6,6	9,3
112,3	113,8	7,5	8,7
102,8	97,4	7,8	8,4
96,5	72,5	7,9	8,6
101,0	82,7	7,8	9,0
98,9	88,9	7,6	9,1
105,1	105,9	7,5	8,7
103,0	100,8	7,6	8,2
99,0	94,0	7,5	7,9
104,3	105,0	7,3	7,9
94,6	58,5	7,6	9,1
90,4	87,6	7,5	9,4
108,9	113,1	7,6	9,5
111,4	112,5	7,9	9,1
100,8	89,6	7,9	9,0
102,5	74,5	8,1	9,3
98,2	82,7	8,2	9,9
98,7	90,1	8,0	9,8
113,3	109,4	7,5	9,4
104,6	96,0	6,8	8,3
99,3	89,2	6,5	8,0
111,8	109,1	6,6	8,5
97,3	49,1	7,6	10,4
97,7	92,9	8,0	11,1
115,6	107,7	8,0	10,9
111,9	103,5	7,7	9,9
107,0	91,1	7,5	9,2
107,1	79,8	7,6	9,2
100,6	71,9	7,7	9,5
99,2	82,9	7,9	9,6
108,4	90,1	7,8	9,5
103,0	100,7	7,5	9,1
99,8	90,7	7,5	8,9
115,0	108,8	7,1	9,0
90,8	44,1	7,5	10,1
95,9	93,6	7,5	10,3
114,4	107,4	7,6	10,2
108,2	96,5	7,7	9,6
112,6	93,6	7,7	9,2
109,1	76,5	7,9	9,3
105,0	76,7	8,1	9,4
105,0	84,0	8,2	9,4
118,5	103,3	8,2	9,2
103,7	88,5	8,1	9,0
112,5	99,0	7,9	9,0
116,6	105,9	7,3	9,0
96,6	44,7	6,9	9,8
101,9	94,0	6,6	10,0
116,5	107,1	6,7	9,9
119,3	104,8	6,9	9,3
115,4	102,5	7,0	9,0
108,5	77,7	7,1	9,0
111,5	85,2	7,2	9,1
108,8	91,3	7,1	9,1
121,8	106,5	6,9	9,1
109,6	92,4	7,0	9,2
112,2	97,5	6,8	8,8
119,6	107,0	6,4	8,3
104,1	51,1	6,7	8,4
105,3	98,6	6,7	8,1
115,0	102,2	6,4	7,8
124,1	114,3	6,3	7,9
116,8	99,4	6,2	7,9
107,5	72,5	6,5	8,0
115,6	92,3	6,8	7,9
116,2	99,4	6,8	7,5
116,3	85,9	6,5	7,2
119,0	109,4	6,3	6,9
111,9	97,6	5,9	6,6
118,6	104,7	5,9	6,7
106,7	56,5	6,4	7,3

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23598&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]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=23598&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23598&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Summary of Dendrogram
Label	Height
1	0.91104335791443
2	0.938083151964682
3	1.10453610171873
4	1.36747943311774
5	1.43178210632764
6	1.45945195193263
7	1.45945195193264
8	1.47648230602333
9	1.54272486205416
10	1.59059737205869
11	1.61864140562386
12	1.67928556237466
13	1.77200451466694
14	1.78325545001269
15	1.88944436276912
16	1.89472953214964
17	1.9544820285692
18	2.06639783197718
19	2.14242852856285
20	2.14941852602046
21	2.35758353862168
22	2.4454038521275
23	2.49198715887542
24	2.61926542649884
25	2.88426245501738
26	2.89076615147303
27	2.94940495590803
28	2.96946033859769
29	3.05704289156166
30	3.22072969855832
31	3.22645316098033
32	3.25115364140177
33	3.28412028998540
34	3.50862201666774
35	3.56214888386368
36	3.63180395946697
37	3.65226833217092
38	3.69188298839495
39	3.77139402040309
40	4.16867005024373
41	4.504435952542
42	4.53789004975673
43	4.54972526643093
44	4.7021271782035
45	4.84659059620743
46	5.25642464038057
47	5.42347776062342
48	5.74934537970728
49	5.99049190107742
50	6.10081961706786
51	6.10982814815606
52	6.49446325510107
53	6.7759984811942
54	7.16190874348874
55	7.20872327691678
56	7.70948683320289
57	7.8675027861693
58	9.77899449072104
59	11.0872538734327
60	13.1794923133258
61	13.9492350527428
62	14.9207282726679
63	16.6732148960125
64	17.0598949438692
65	17.6931122913625
66	19.3527090773789
67	20.9498199775892
68	21.1252578305688
69	23.7373182542812
70	28.1448653557398
71	31.5072474422490
72	35.1541200481976
73	46.850013212842
74	87.8217584585704
75	111.256617875142
76	141.408475710082
77	269.862549698179
78	537.930427161591

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 0.91104335791443 \tabularnewline
2 & 0.938083151964682 \tabularnewline
3 & 1.10453610171873 \tabularnewline
4 & 1.36747943311774 \tabularnewline
5 & 1.43178210632764 \tabularnewline
6 & 1.45945195193263 \tabularnewline
7 & 1.45945195193264 \tabularnewline
8 & 1.47648230602333 \tabularnewline
9 & 1.54272486205416 \tabularnewline
10 & 1.59059737205869 \tabularnewline
11 & 1.61864140562386 \tabularnewline
12 & 1.67928556237466 \tabularnewline
13 & 1.77200451466694 \tabularnewline
14 & 1.78325545001269 \tabularnewline
15 & 1.88944436276912 \tabularnewline
16 & 1.89472953214964 \tabularnewline
17 & 1.9544820285692 \tabularnewline
18 & 2.06639783197718 \tabularnewline
19 & 2.14242852856285 \tabularnewline
20 & 2.14941852602046 \tabularnewline
21 & 2.35758353862168 \tabularnewline
22 & 2.4454038521275 \tabularnewline
23 & 2.49198715887542 \tabularnewline
24 & 2.61926542649884 \tabularnewline
25 & 2.88426245501738 \tabularnewline
26 & 2.89076615147303 \tabularnewline
27 & 2.94940495590803 \tabularnewline
28 & 2.96946033859769 \tabularnewline
29 & 3.05704289156166 \tabularnewline
30 & 3.22072969855832 \tabularnewline
31 & 3.22645316098033 \tabularnewline
32 & 3.25115364140177 \tabularnewline
33 & 3.28412028998540 \tabularnewline
34 & 3.50862201666774 \tabularnewline
35 & 3.56214888386368 \tabularnewline
36 & 3.63180395946697 \tabularnewline
37 & 3.65226833217092 \tabularnewline
38 & 3.69188298839495 \tabularnewline
39 & 3.77139402040309 \tabularnewline
40 & 4.16867005024373 \tabularnewline
41 & 4.504435952542 \tabularnewline
42 & 4.53789004975673 \tabularnewline
43 & 4.54972526643093 \tabularnewline
44 & 4.7021271782035 \tabularnewline
45 & 4.84659059620743 \tabularnewline
46 & 5.25642464038057 \tabularnewline
47 & 5.42347776062342 \tabularnewline
48 & 5.74934537970728 \tabularnewline
49 & 5.99049190107742 \tabularnewline
50 & 6.10081961706786 \tabularnewline
51 & 6.10982814815606 \tabularnewline
52 & 6.49446325510107 \tabularnewline
53 & 6.7759984811942 \tabularnewline
54 & 7.16190874348874 \tabularnewline
55 & 7.20872327691678 \tabularnewline
56 & 7.70948683320289 \tabularnewline
57 & 7.8675027861693 \tabularnewline
58 & 9.77899449072104 \tabularnewline
59 & 11.0872538734327 \tabularnewline
60 & 13.1794923133258 \tabularnewline
61 & 13.9492350527428 \tabularnewline
62 & 14.9207282726679 \tabularnewline
63 & 16.6732148960125 \tabularnewline
64 & 17.0598949438692 \tabularnewline
65 & 17.6931122913625 \tabularnewline
66 & 19.3527090773789 \tabularnewline
67 & 20.9498199775892 \tabularnewline
68 & 21.1252578305688 \tabularnewline
69 & 23.7373182542812 \tabularnewline
70 & 28.1448653557398 \tabularnewline
71 & 31.5072474422490 \tabularnewline
72 & 35.1541200481976 \tabularnewline
73 & 46.850013212842 \tabularnewline
74 & 87.8217584585704 \tabularnewline
75 & 111.256617875142 \tabularnewline
76 & 141.408475710082 \tabularnewline
77 & 269.862549698179 \tabularnewline
78 & 537.930427161591 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23598&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]0.91104335791443[/C][/ROW]
[ROW][C]2[/C][C]0.938083151964682[/C][/ROW]
[ROW][C]3[/C][C]1.10453610171873[/C][/ROW]
[ROW][C]4[/C][C]1.36747943311774[/C][/ROW]
[ROW][C]5[/C][C]1.43178210632764[/C][/ROW]
[ROW][C]6[/C][C]1.45945195193263[/C][/ROW]
[ROW][C]7[/C][C]1.45945195193264[/C][/ROW]
[ROW][C]8[/C][C]1.47648230602333[/C][/ROW]
[ROW][C]9[/C][C]1.54272486205416[/C][/ROW]
[ROW][C]10[/C][C]1.59059737205869[/C][/ROW]
[ROW][C]11[/C][C]1.61864140562386[/C][/ROW]
[ROW][C]12[/C][C]1.67928556237466[/C][/ROW]
[ROW][C]13[/C][C]1.77200451466694[/C][/ROW]
[ROW][C]14[/C][C]1.78325545001269[/C][/ROW]
[ROW][C]15[/C][C]1.88944436276912[/C][/ROW]
[ROW][C]16[/C][C]1.89472953214964[/C][/ROW]
[ROW][C]17[/C][C]1.9544820285692[/C][/ROW]
[ROW][C]18[/C][C]2.06639783197718[/C][/ROW]
[ROW][C]19[/C][C]2.14242852856285[/C][/ROW]
[ROW][C]20[/C][C]2.14941852602046[/C][/ROW]
[ROW][C]21[/C][C]2.35758353862168[/C][/ROW]
[ROW][C]22[/C][C]2.4454038521275[/C][/ROW]
[ROW][C]23[/C][C]2.49198715887542[/C][/ROW]
[ROW][C]24[/C][C]2.61926542649884[/C][/ROW]
[ROW][C]25[/C][C]2.88426245501738[/C][/ROW]
[ROW][C]26[/C][C]2.89076615147303[/C][/ROW]
[ROW][C]27[/C][C]2.94940495590803[/C][/ROW]
[ROW][C]28[/C][C]2.96946033859769[/C][/ROW]
[ROW][C]29[/C][C]3.05704289156166[/C][/ROW]
[ROW][C]30[/C][C]3.22072969855832[/C][/ROW]
[ROW][C]31[/C][C]3.22645316098033[/C][/ROW]
[ROW][C]32[/C][C]3.25115364140177[/C][/ROW]
[ROW][C]33[/C][C]3.28412028998540[/C][/ROW]
[ROW][C]34[/C][C]3.50862201666774[/C][/ROW]
[ROW][C]35[/C][C]3.56214888386368[/C][/ROW]
[ROW][C]36[/C][C]3.63180395946697[/C][/ROW]
[ROW][C]37[/C][C]3.65226833217092[/C][/ROW]
[ROW][C]38[/C][C]3.69188298839495[/C][/ROW]
[ROW][C]39[/C][C]3.77139402040309[/C][/ROW]
[ROW][C]40[/C][C]4.16867005024373[/C][/ROW]
[ROW][C]41[/C][C]4.504435952542[/C][/ROW]
[ROW][C]42[/C][C]4.53789004975673[/C][/ROW]
[ROW][C]43[/C][C]4.54972526643093[/C][/ROW]
[ROW][C]44[/C][C]4.7021271782035[/C][/ROW]
[ROW][C]45[/C][C]4.84659059620743[/C][/ROW]
[ROW][C]46[/C][C]5.25642464038057[/C][/ROW]
[ROW][C]47[/C][C]5.42347776062342[/C][/ROW]
[ROW][C]48[/C][C]5.74934537970728[/C][/ROW]
[ROW][C]49[/C][C]5.99049190107742[/C][/ROW]
[ROW][C]50[/C][C]6.10081961706786[/C][/ROW]
[ROW][C]51[/C][C]6.10982814815606[/C][/ROW]
[ROW][C]52[/C][C]6.49446325510107[/C][/ROW]
[ROW][C]53[/C][C]6.7759984811942[/C][/ROW]
[ROW][C]54[/C][C]7.16190874348874[/C][/ROW]
[ROW][C]55[/C][C]7.20872327691678[/C][/ROW]
[ROW][C]56[/C][C]7.70948683320289[/C][/ROW]
[ROW][C]57[/C][C]7.8675027861693[/C][/ROW]
[ROW][C]58[/C][C]9.77899449072104[/C][/ROW]
[ROW][C]59[/C][C]11.0872538734327[/C][/ROW]
[ROW][C]60[/C][C]13.1794923133258[/C][/ROW]
[ROW][C]61[/C][C]13.9492350527428[/C][/ROW]
[ROW][C]62[/C][C]14.9207282726679[/C][/ROW]
[ROW][C]63[/C][C]16.6732148960125[/C][/ROW]
[ROW][C]64[/C][C]17.0598949438692[/C][/ROW]
[ROW][C]65[/C][C]17.6931122913625[/C][/ROW]
[ROW][C]66[/C][C]19.3527090773789[/C][/ROW]
[ROW][C]67[/C][C]20.9498199775892[/C][/ROW]
[ROW][C]68[/C][C]21.1252578305688[/C][/ROW]
[ROW][C]69[/C][C]23.7373182542812[/C][/ROW]
[ROW][C]70[/C][C]28.1448653557398[/C][/ROW]
[ROW][C]71[/C][C]31.5072474422490[/C][/ROW]
[ROW][C]72[/C][C]35.1541200481976[/C][/ROW]
[ROW][C]73[/C][C]46.850013212842[/C][/ROW]
[ROW][C]74[/C][C]87.8217584585704[/C][/ROW]
[ROW][C]75[/C][C]111.256617875142[/C][/ROW]
[ROW][C]76[/C][C]141.408475710082[/C][/ROW]
[ROW][C]77[/C][C]269.862549698179[/C][/ROW]
[ROW][C]78[/C][C]537.930427161591[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23598&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23598&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
Label	Height
1	0.91104335791443
2	0.938083151964682
3	1.10453610171873
4	1.36747943311774
5	1.43178210632764
6	1.45945195193263
7	1.45945195193264
8	1.47648230602333
9	1.54272486205416
10	1.59059737205869
11	1.61864140562386
12	1.67928556237466
13	1.77200451466694
14	1.78325545001269
15	1.88944436276912
16	1.89472953214964
17	1.9544820285692
18	2.06639783197718
19	2.14242852856285
20	2.14941852602046
21	2.35758353862168
22	2.4454038521275
23	2.49198715887542
24	2.61926542649884
25	2.88426245501738
26	2.89076615147303
27	2.94940495590803
28	2.96946033859769
29	3.05704289156166
30	3.22072969855832
31	3.22645316098033
32	3.25115364140177
33	3.28412028998540
34	3.50862201666774
35	3.56214888386368
36	3.63180395946697
37	3.65226833217092
38	3.69188298839495
39	3.77139402040309
40	4.16867005024373
41	4.504435952542
42	4.53789004975673
43	4.54972526643093
44	4.7021271782035
45	4.84659059620743
46	5.25642464038057
47	5.42347776062342
48	5.74934537970728
49	5.99049190107742
50	6.10081961706786
51	6.10982814815606
52	6.49446325510107
53	6.7759984811942
54	7.16190874348874
55	7.20872327691678
56	7.70948683320289
57	7.8675027861693
58	9.77899449072104
59	11.0872538734327
60	13.1794923133258
61	13.9492350527428
62	14.9207282726679
63	16.6732148960125
64	17.0598949438692
65	17.6931122913625
66	19.3527090773789
67	20.9498199775892
68	21.1252578305688
69	23.7373182542812
70	28.1448653557398
71	31.5072474422490
72	35.1541200481976
73	46.850013212842
74	87.8217584585704
75	111.256617875142
76	141.408475710082
77	269.862549698179
78	537.930427161591

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code