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Author's title

Author*Unverified author*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationMon, 17 Dec 2007 03:37:19 -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/Dec/17/t1197887027ro59nvlt9xad3c7.htm/, Retrieved Fri, 03 May 2024 19:55:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4330, Retrieved Fri, 03 May 2024 19:55:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact182
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Hierarchical Clustering] [cluster van alle ...] [2007-12-17 10:37:19] [bd02e85be52eb1cb060a2c60779eb820] [Current]
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Dataseries X:
51978	88900	37702	124,9
50330	87280	30364	132
48538	85519	32609	151,4
46636	83647	30212	108,9
44574	81616	29965	121,3
43028	80100	28352	123,4
56924	94027	25814	90,3
65193	102327	22414	79,3
67132	104296	20506	117,2
64398	101593	28806	116,9
57591	94816	22228	120,8
56279	93535	13971	96,1
56331	93618	36845	100,8
55015	92330	35338	105,3
53405	90751	35022	116,1
51200	88576	34777	112,8
48695	86102	26887	114,5
48057	85494	23970	117,2
65964	103432	22780	77,1
71371	108870	17351	80,1
72184	109713	21382	120,3
69400	106960	24561	133,4
65605	103195	17409	109,4
64727	102348	11514	93,2
64506	102158	31514	91,2
62751	100431	27071	99,2
59938	97649	29462	108,2
57870	95611	26105	101,5
55263	93035	22397	106,9
55777	93579	23843	104,4
73944	111777	21705	77,9
78201	116065	18089	60
78715	116609	20764	99,5
75009	112934	25316	95
69705	107660	17704	105,6
69979	107965	15548	102,5
69755	107772	28029	93,3
68155	106201	29383	97,3
64211	102288	36438	127
61110	99217	32034	111,7
58373	96511	22679	96,4
58288	96456	24319	133
74822	113021	18004	72,2
79606	117836	17537	95,8
80232	118492	20366	124,1
75631	113922	22782	127,6
70996	109317	19169	110,7
69144	107496	13807	104,6
67141	105524	29743	112,7
65413	103824	25591	115,3
63391	101833	29096	139,4
60964	99436	26482	119
58412	96915	22405	97,4
57539	96072	27044	154
73377	111941	17970	81,5
77413	116008	18730	88,8
78932	117557	19684	127,7
74789	113445	19785	105,1
70076	108762	18479	114,9
67944	106661	10698	106,4
64076	102824	31956	104,5
63136	101912	29506	121,6
60198	99005	34506	141,4
59057	97894	27165	99
57388	96256	26736	126,7
56708	95606	23691	134,1
70019	108948	18157	81,3
72263	111223	17328	88,6
74152	113142	18205	132,7
67057	106078	20995	132,9
61941	100992	17382	134,4
58331	97413	9367	103,7




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4330&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4330&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4330&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Summary of Dendrogram
LabelHeight
1377.700886946271
2390.213134069062
3489.574141473996
4489.708076306691
5712.462104255377
6907.742744394027
71017.79341715301
81271.36232443784
91284.41959520127
101396.21876509378
111453.61213533735
121472.66235437727
131538.99118423168
141628.20583772446
151695.08041671372
161849.46383852186
171882.64040379463
181987.02576983793
192085.13496056577
202128.54575708393
212137.11233034111
222147.94212030402
232247.44431231316
242277.12837582777
252309.60782067277
262472.34294546691
272643.5495247867
282700.0269276435
292731.99977306002
302790.20550497629
312976.18178002450
323044.01567177306
333047.22895267159
343168.67023347073
353275.09313693055
363369.38961237789
373579.66492985028
383808.28646172181
393816.48913715493
404275.4483975368
414456.42461588923
424630.2768119749
434886.19271678131
445240.61522765135
455336.50135553224
465513.48744439589
476244.50076378228
486359.75327823336
496392.36948724856
506656.13457569718
516941.02182434739
527012.09616449941
537515.83100542274
548200.59887240791
559512.82729860415
5610906.8237233396
5712736.2281429191
5812772.8081249439
5912934.3236195214
6013352.0001280653
6116806.3382116651
6218101.6314345557
6330828.05902107
6432549.2088911025
6533381.6000160049
6645157.085833294
6745648.5021435523
6878524.5442908288
69110811.067975235
70153807.199288475
71469118.331558065

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 377.700886946271 \tabularnewline
2 & 390.213134069062 \tabularnewline
3 & 489.574141473996 \tabularnewline
4 & 489.708076306691 \tabularnewline
5 & 712.462104255377 \tabularnewline
6 & 907.742744394027 \tabularnewline
7 & 1017.79341715301 \tabularnewline
8 & 1271.36232443784 \tabularnewline
9 & 1284.41959520127 \tabularnewline
10 & 1396.21876509378 \tabularnewline
11 & 1453.61213533735 \tabularnewline
12 & 1472.66235437727 \tabularnewline
13 & 1538.99118423168 \tabularnewline
14 & 1628.20583772446 \tabularnewline
15 & 1695.08041671372 \tabularnewline
16 & 1849.46383852186 \tabularnewline
17 & 1882.64040379463 \tabularnewline
18 & 1987.02576983793 \tabularnewline
19 & 2085.13496056577 \tabularnewline
20 & 2128.54575708393 \tabularnewline
21 & 2137.11233034111 \tabularnewline
22 & 2147.94212030402 \tabularnewline
23 & 2247.44431231316 \tabularnewline
24 & 2277.12837582777 \tabularnewline
25 & 2309.60782067277 \tabularnewline
26 & 2472.34294546691 \tabularnewline
27 & 2643.5495247867 \tabularnewline
28 & 2700.0269276435 \tabularnewline
29 & 2731.99977306002 \tabularnewline
30 & 2790.20550497629 \tabularnewline
31 & 2976.18178002450 \tabularnewline
32 & 3044.01567177306 \tabularnewline
33 & 3047.22895267159 \tabularnewline
34 & 3168.67023347073 \tabularnewline
35 & 3275.09313693055 \tabularnewline
36 & 3369.38961237789 \tabularnewline
37 & 3579.66492985028 \tabularnewline
38 & 3808.28646172181 \tabularnewline
39 & 3816.48913715493 \tabularnewline
40 & 4275.4483975368 \tabularnewline
41 & 4456.42461588923 \tabularnewline
42 & 4630.2768119749 \tabularnewline
43 & 4886.19271678131 \tabularnewline
44 & 5240.61522765135 \tabularnewline
45 & 5336.50135553224 \tabularnewline
46 & 5513.48744439589 \tabularnewline
47 & 6244.50076378228 \tabularnewline
48 & 6359.75327823336 \tabularnewline
49 & 6392.36948724856 \tabularnewline
50 & 6656.13457569718 \tabularnewline
51 & 6941.02182434739 \tabularnewline
52 & 7012.09616449941 \tabularnewline
53 & 7515.83100542274 \tabularnewline
54 & 8200.59887240791 \tabularnewline
55 & 9512.82729860415 \tabularnewline
56 & 10906.8237233396 \tabularnewline
57 & 12736.2281429191 \tabularnewline
58 & 12772.8081249439 \tabularnewline
59 & 12934.3236195214 \tabularnewline
60 & 13352.0001280653 \tabularnewline
61 & 16806.3382116651 \tabularnewline
62 & 18101.6314345557 \tabularnewline
63 & 30828.05902107 \tabularnewline
64 & 32549.2088911025 \tabularnewline
65 & 33381.6000160049 \tabularnewline
66 & 45157.085833294 \tabularnewline
67 & 45648.5021435523 \tabularnewline
68 & 78524.5442908288 \tabularnewline
69 & 110811.067975235 \tabularnewline
70 & 153807.199288475 \tabularnewline
71 & 469118.331558065 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4330&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]377.700886946271[/C][/ROW]
[ROW][C]2[/C][C]390.213134069062[/C][/ROW]
[ROW][C]3[/C][C]489.574141473996[/C][/ROW]
[ROW][C]4[/C][C]489.708076306691[/C][/ROW]
[ROW][C]5[/C][C]712.462104255377[/C][/ROW]
[ROW][C]6[/C][C]907.742744394027[/C][/ROW]
[ROW][C]7[/C][C]1017.79341715301[/C][/ROW]
[ROW][C]8[/C][C]1271.36232443784[/C][/ROW]
[ROW][C]9[/C][C]1284.41959520127[/C][/ROW]
[ROW][C]10[/C][C]1396.21876509378[/C][/ROW]
[ROW][C]11[/C][C]1453.61213533735[/C][/ROW]
[ROW][C]12[/C][C]1472.66235437727[/C][/ROW]
[ROW][C]13[/C][C]1538.99118423168[/C][/ROW]
[ROW][C]14[/C][C]1628.20583772446[/C][/ROW]
[ROW][C]15[/C][C]1695.08041671372[/C][/ROW]
[ROW][C]16[/C][C]1849.46383852186[/C][/ROW]
[ROW][C]17[/C][C]1882.64040379463[/C][/ROW]
[ROW][C]18[/C][C]1987.02576983793[/C][/ROW]
[ROW][C]19[/C][C]2085.13496056577[/C][/ROW]
[ROW][C]20[/C][C]2128.54575708393[/C][/ROW]
[ROW][C]21[/C][C]2137.11233034111[/C][/ROW]
[ROW][C]22[/C][C]2147.94212030402[/C][/ROW]
[ROW][C]23[/C][C]2247.44431231316[/C][/ROW]
[ROW][C]24[/C][C]2277.12837582777[/C][/ROW]
[ROW][C]25[/C][C]2309.60782067277[/C][/ROW]
[ROW][C]26[/C][C]2472.34294546691[/C][/ROW]
[ROW][C]27[/C][C]2643.5495247867[/C][/ROW]
[ROW][C]28[/C][C]2700.0269276435[/C][/ROW]
[ROW][C]29[/C][C]2731.99977306002[/C][/ROW]
[ROW][C]30[/C][C]2790.20550497629[/C][/ROW]
[ROW][C]31[/C][C]2976.18178002450[/C][/ROW]
[ROW][C]32[/C][C]3044.01567177306[/C][/ROW]
[ROW][C]33[/C][C]3047.22895267159[/C][/ROW]
[ROW][C]34[/C][C]3168.67023347073[/C][/ROW]
[ROW][C]35[/C][C]3275.09313693055[/C][/ROW]
[ROW][C]36[/C][C]3369.38961237789[/C][/ROW]
[ROW][C]37[/C][C]3579.66492985028[/C][/ROW]
[ROW][C]38[/C][C]3808.28646172181[/C][/ROW]
[ROW][C]39[/C][C]3816.48913715493[/C][/ROW]
[ROW][C]40[/C][C]4275.4483975368[/C][/ROW]
[ROW][C]41[/C][C]4456.42461588923[/C][/ROW]
[ROW][C]42[/C][C]4630.2768119749[/C][/ROW]
[ROW][C]43[/C][C]4886.19271678131[/C][/ROW]
[ROW][C]44[/C][C]5240.61522765135[/C][/ROW]
[ROW][C]45[/C][C]5336.50135553224[/C][/ROW]
[ROW][C]46[/C][C]5513.48744439589[/C][/ROW]
[ROW][C]47[/C][C]6244.50076378228[/C][/ROW]
[ROW][C]48[/C][C]6359.75327823336[/C][/ROW]
[ROW][C]49[/C][C]6392.36948724856[/C][/ROW]
[ROW][C]50[/C][C]6656.13457569718[/C][/ROW]
[ROW][C]51[/C][C]6941.02182434739[/C][/ROW]
[ROW][C]52[/C][C]7012.09616449941[/C][/ROW]
[ROW][C]53[/C][C]7515.83100542274[/C][/ROW]
[ROW][C]54[/C][C]8200.59887240791[/C][/ROW]
[ROW][C]55[/C][C]9512.82729860415[/C][/ROW]
[ROW][C]56[/C][C]10906.8237233396[/C][/ROW]
[ROW][C]57[/C][C]12736.2281429191[/C][/ROW]
[ROW][C]58[/C][C]12772.8081249439[/C][/ROW]
[ROW][C]59[/C][C]12934.3236195214[/C][/ROW]
[ROW][C]60[/C][C]13352.0001280653[/C][/ROW]
[ROW][C]61[/C][C]16806.3382116651[/C][/ROW]
[ROW][C]62[/C][C]18101.6314345557[/C][/ROW]
[ROW][C]63[/C][C]30828.05902107[/C][/ROW]
[ROW][C]64[/C][C]32549.2088911025[/C][/ROW]
[ROW][C]65[/C][C]33381.6000160049[/C][/ROW]
[ROW][C]66[/C][C]45157.085833294[/C][/ROW]
[ROW][C]67[/C][C]45648.5021435523[/C][/ROW]
[ROW][C]68[/C][C]78524.5442908288[/C][/ROW]
[ROW][C]69[/C][C]110811.067975235[/C][/ROW]
[ROW][C]70[/C][C]153807.199288475[/C][/ROW]
[ROW][C]71[/C][C]469118.331558065[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4330&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4330&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
1377.700886946271
2390.213134069062
3489.574141473996
4489.708076306691
5712.462104255377
6907.742744394027
71017.79341715301
81271.36232443784
91284.41959520127
101396.21876509378
111453.61213533735
121472.66235437727
131538.99118423168
141628.20583772446
151695.08041671372
161849.46383852186
171882.64040379463
181987.02576983793
192085.13496056577
202128.54575708393
212137.11233034111
222147.94212030402
232247.44431231316
242277.12837582777
252309.60782067277
262472.34294546691
272643.5495247867
282700.0269276435
292731.99977306002
302790.20550497629
312976.18178002450
323044.01567177306
333047.22895267159
343168.67023347073
353275.09313693055
363369.38961237789
373579.66492985028
383808.28646172181
393816.48913715493
404275.4483975368
414456.42461588923
424630.2768119749
434886.19271678131
445240.61522765135
455336.50135553224
465513.48744439589
476244.50076378228
486359.75327823336
496392.36948724856
506656.13457569718
516941.02182434739
527012.09616449941
537515.83100542274
548200.59887240791
559512.82729860415
5610906.8237233396
5712736.2281429191
5812772.8081249439
5912934.3236195214
6013352.0001280653
6116806.3382116651
6218101.6314345557
6330828.05902107
6432549.2088911025
6533381.6000160049
6645157.085833294
6745648.5021435523
6878524.5442908288
69110811.067975235
70153807.199288475
71469118.331558065



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')
}