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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 computationSun, 04 Nov 2007 13:27:01 -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/Nov/04/0z73zq2j1wgotmp1194207923.htm/, Retrieved Sun, 05 May 2024 16:24:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263, Retrieved Sun, 05 May 2024 16:24:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact226

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Hierarchical Clustering] [Hierarchical clus...] [2007-11-04 20:27:01] [7c5c775a3769ba2649d285a4261e023c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
542	3820,33	115,9
565	3765,56	112,9
555	3794,29	126,3
499	3946,98	116,8
511	3933,16	112,0
526	3858,21	129,7
532	3708,80	113,6
549	3665,08	115,7
561	3760,90	119,5
557	3697,22	125,8
566	3602,00	129,6
588	3669,15	128,0
620	3551,04	112,8
626	3522,89	101,6
620	3449,15	123,9
573	3378,85	118,8
573	3359,05	109,1
574	3536,20	130,6
580	3507,13	112,4
590	3469,48	111,0
593	3446,17	116,2
597	3349,10	119,8
595	3264,53	117,2
612	3201,79	127,3
628	3261,30	107,7
629	3114,31	97,5
621	3139,50	120,1
569	3036,54	110,6
567	2934,75	111,3
573	2817,41	119,8
584	2866,08	105,5
589	2892,56	108,7
591	2819,19	128,7
595	2774,77	119,5
594	2737,67	121,1
611	2692,06	128,4
613	2668,47	108,8
611	2620,03	107,5
594	2650,24	125,6
543	2687,68	102,9
537	2669,36	107,5
544	2707,69	120,4
555	2663,32	104,3
561	2748,50	100,6
562	2696,28	121,9
555	2660,37	112,7
547	2567,13	124,9
565	2537,84	123,9
578	2386,92	102,2
580	2479,57	104,9
569	2474,07	109,8
507	2395,47	98,9
501	2315,49	107,3
509	2318,54	112,6
510	2098,89	104,0
517	2165,44	110,6
519	2237,74	100,8
512	2407,87	103,8
509	2663,49	117,0
519	2561,29	108,4

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263&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]1 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=263&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Summary of Dendrogram
LabelHeight
18.90294894964594
29.01529810932498
310.0693842910081
413.2385799842732
514.2397331435671
618.9217441056580
719.8187386076912
820.1588293310897
921.3644119975252
1022.0483559477796
1124.0706481009548
1227.1372511504021
1330.1319830080931
1430.7351281110069
1530.8846644793173
1630.9069830297297
1733.0205330059949
1834.4917801802111
1934.7749349388321
2034.8181691075218
2134.9518519823346
2236.4439977870805
2336.8737713807682
2437.1479474533923
2539.1056786157711
2641.0956798216066
2745.7973097793218
2847.8612324925695
2954.5520301839121
3061.171529016414
3165.0614598419683
3265.4627247458267
3367.2418210639779
3470.0427781421215
3573.1633905416791
3675.4678353207801
3778.0117160559894
3889.1552689435473
39104.868737093584
40108.460174416164
41114.302736135854
42119.61646506047
43131.629447114539
44169.147273068071
45218.406132277020
46222.052099663075
47235.333217187734
48291.416748372582
49307.614639579902
50345.749028822710
51475.561698085874
52511.705090756845
53571.945685271102
54701.861534816066
551251.19718955184
561516.15355587277
573274.14943533176
583648.87896583168
5920140.4564865208

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 8.90294894964594 \tabularnewline
2 & 9.01529810932498 \tabularnewline
3 & 10.0693842910081 \tabularnewline
4 & 13.2385799842732 \tabularnewline
5 & 14.2397331435671 \tabularnewline
6 & 18.9217441056580 \tabularnewline
7 & 19.8187386076912 \tabularnewline
8 & 20.1588293310897 \tabularnewline
9 & 21.3644119975252 \tabularnewline
10 & 22.0483559477796 \tabularnewline
11 & 24.0706481009548 \tabularnewline
12 & 27.1372511504021 \tabularnewline
13 & 30.1319830080931 \tabularnewline
14 & 30.7351281110069 \tabularnewline
15 & 30.8846644793173 \tabularnewline
16 & 30.9069830297297 \tabularnewline
17 & 33.0205330059949 \tabularnewline
18 & 34.4917801802111 \tabularnewline
19 & 34.7749349388321 \tabularnewline
20 & 34.8181691075218 \tabularnewline
21 & 34.9518519823346 \tabularnewline
22 & 36.4439977870805 \tabularnewline
23 & 36.8737713807682 \tabularnewline
24 & 37.1479474533923 \tabularnewline
25 & 39.1056786157711 \tabularnewline
26 & 41.0956798216066 \tabularnewline
27 & 45.7973097793218 \tabularnewline
28 & 47.8612324925695 \tabularnewline
29 & 54.5520301839121 \tabularnewline
30 & 61.171529016414 \tabularnewline
31 & 65.0614598419683 \tabularnewline
32 & 65.4627247458267 \tabularnewline
33 & 67.2418210639779 \tabularnewline
34 & 70.0427781421215 \tabularnewline
35 & 73.1633905416791 \tabularnewline
36 & 75.4678353207801 \tabularnewline
37 & 78.0117160559894 \tabularnewline
38 & 89.1552689435473 \tabularnewline
39 & 104.868737093584 \tabularnewline
40 & 108.460174416164 \tabularnewline
41 & 114.302736135854 \tabularnewline
42 & 119.61646506047 \tabularnewline
43 & 131.629447114539 \tabularnewline
44 & 169.147273068071 \tabularnewline
45 & 218.406132277020 \tabularnewline
46 & 222.052099663075 \tabularnewline
47 & 235.333217187734 \tabularnewline
48 & 291.416748372582 \tabularnewline
49 & 307.614639579902 \tabularnewline
50 & 345.749028822710 \tabularnewline
51 & 475.561698085874 \tabularnewline
52 & 511.705090756845 \tabularnewline
53 & 571.945685271102 \tabularnewline
54 & 701.861534816066 \tabularnewline
55 & 1251.19718955184 \tabularnewline
56 & 1516.15355587277 \tabularnewline
57 & 3274.14943533176 \tabularnewline
58 & 3648.87896583168 \tabularnewline
59 & 20140.4564865208 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]8.90294894964594[/C][/ROW]
[ROW][C]2[/C][C]9.01529810932498[/C][/ROW]
[ROW][C]3[/C][C]10.0693842910081[/C][/ROW]
[ROW][C]4[/C][C]13.2385799842732[/C][/ROW]
[ROW][C]5[/C][C]14.2397331435671[/C][/ROW]
[ROW][C]6[/C][C]18.9217441056580[/C][/ROW]
[ROW][C]7[/C][C]19.8187386076912[/C][/ROW]
[ROW][C]8[/C][C]20.1588293310897[/C][/ROW]
[ROW][C]9[/C][C]21.3644119975252[/C][/ROW]
[ROW][C]10[/C][C]22.0483559477796[/C][/ROW]
[ROW][C]11[/C][C]24.0706481009548[/C][/ROW]
[ROW][C]12[/C][C]27.1372511504021[/C][/ROW]
[ROW][C]13[/C][C]30.1319830080931[/C][/ROW]
[ROW][C]14[/C][C]30.7351281110069[/C][/ROW]
[ROW][C]15[/C][C]30.8846644793173[/C][/ROW]
[ROW][C]16[/C][C]30.9069830297297[/C][/ROW]
[ROW][C]17[/C][C]33.0205330059949[/C][/ROW]
[ROW][C]18[/C][C]34.4917801802111[/C][/ROW]
[ROW][C]19[/C][C]34.7749349388321[/C][/ROW]
[ROW][C]20[/C][C]34.8181691075218[/C][/ROW]
[ROW][C]21[/C][C]34.9518519823346[/C][/ROW]
[ROW][C]22[/C][C]36.4439977870805[/C][/ROW]
[ROW][C]23[/C][C]36.8737713807682[/C][/ROW]
[ROW][C]24[/C][C]37.1479474533923[/C][/ROW]
[ROW][C]25[/C][C]39.1056786157711[/C][/ROW]
[ROW][C]26[/C][C]41.0956798216066[/C][/ROW]
[ROW][C]27[/C][C]45.7973097793218[/C][/ROW]
[ROW][C]28[/C][C]47.8612324925695[/C][/ROW]
[ROW][C]29[/C][C]54.5520301839121[/C][/ROW]
[ROW][C]30[/C][C]61.171529016414[/C][/ROW]
[ROW][C]31[/C][C]65.0614598419683[/C][/ROW]
[ROW][C]32[/C][C]65.4627247458267[/C][/ROW]
[ROW][C]33[/C][C]67.2418210639779[/C][/ROW]
[ROW][C]34[/C][C]70.0427781421215[/C][/ROW]
[ROW][C]35[/C][C]73.1633905416791[/C][/ROW]
[ROW][C]36[/C][C]75.4678353207801[/C][/ROW]
[ROW][C]37[/C][C]78.0117160559894[/C][/ROW]
[ROW][C]38[/C][C]89.1552689435473[/C][/ROW]
[ROW][C]39[/C][C]104.868737093584[/C][/ROW]
[ROW][C]40[/C][C]108.460174416164[/C][/ROW]
[ROW][C]41[/C][C]114.302736135854[/C][/ROW]
[ROW][C]42[/C][C]119.61646506047[/C][/ROW]
[ROW][C]43[/C][C]131.629447114539[/C][/ROW]
[ROW][C]44[/C][C]169.147273068071[/C][/ROW]
[ROW][C]45[/C][C]218.406132277020[/C][/ROW]
[ROW][C]46[/C][C]222.052099663075[/C][/ROW]
[ROW][C]47[/C][C]235.333217187734[/C][/ROW]
[ROW][C]48[/C][C]291.416748372582[/C][/ROW]
[ROW][C]49[/C][C]307.614639579902[/C][/ROW]
[ROW][C]50[/C][C]345.749028822710[/C][/ROW]
[ROW][C]51[/C][C]475.561698085874[/C][/ROW]
[ROW][C]52[/C][C]511.705090756845[/C][/ROW]
[ROW][C]53[/C][C]571.945685271102[/C][/ROW]
[ROW][C]54[/C][C]701.861534816066[/C][/ROW]
[ROW][C]55[/C][C]1251.19718955184[/C][/ROW]
[ROW][C]56[/C][C]1516.15355587277[/C][/ROW]
[ROW][C]57[/C][C]3274.14943533176[/C][/ROW]
[ROW][C]58[/C][C]3648.87896583168[/C][/ROW]
[ROW][C]59[/C][C]20140.4564865208[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263&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
18.90294894964594
29.01529810932498
310.0693842910081
413.2385799842732
514.2397331435671
618.9217441056580
719.8187386076912
820.1588293310897
921.3644119975252
1022.0483559477796
1124.0706481009548
1227.1372511504021
1330.1319830080931
1430.7351281110069
1530.8846644793173
1630.9069830297297
1733.0205330059949
1834.4917801802111
1934.7749349388321
2034.8181691075218
2134.9518519823346
2236.4439977870805
2336.8737713807682
2437.1479474533923
2539.1056786157711
2641.0956798216066
2745.7973097793218
2847.8612324925695
2954.5520301839121
3061.171529016414
3165.0614598419683
3265.4627247458267
3367.2418210639779
3470.0427781421215
3573.1633905416791
3675.4678353207801
3778.0117160559894
3889.1552689435473
39104.868737093584
40108.460174416164
41114.302736135854
42119.61646506047
43131.629447114539
44169.147273068071
45218.406132277020
46222.052099663075
47235.333217187734
48291.416748372582
49307.614639579902
50345.749028822710
51475.561698085874
52511.705090756845
53571.945685271102
54701.861534816066
551251.19718955184
561516.15355587277
573274.14943533176
583648.87896583168
5920140.4564865208


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')
}