Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationTue, 11 Nov 2008 05:35:40 -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/11/t1226407000muj3g3yesbfx04f.htm/, Retrieved Sun, 19 May 2024 10:48:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23397, Retrieved Sun, 19 May 2024 10:48:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Hierarchical Clustering] [Q2 Hierarchical C...] [2008-11-11 12:35:40] [21d7d81e7693ad6dde5aadefb1046611] [Current]
Feedback Forum

Post a new message
Dataseries X:
604.4	882.5	1.1663
883.9	789.6	1.1372
527.9	773.3	1.1139
756.2	804.3	1.1222
812.9	817.8	1.1692
655.6	836.7	1.1702
707.6	721.8	1.2286
612.6	760.8	1.2613
659.2	841.4	1.2646
833.4	1045.6	1.2262
727.8	949.2	1.1985
797.2	850.1	1.2007
753	957.4	1.2138
762	851.8	1.2266
613.7	913.9	1.2176
759.2	888	1.2218
816.4	973.8	1.249
736.8	927.6	1.2991
680.1	833	1.3408
736.5	879.5	1.3119
637.2	797.3	1.3014
801.9	834.5	1.3201
772.3	735.1	1.2938
897.3	835	1.2694
792.1	892.8	1.2165
826.8	697.2	1.2037
666.8	821.1	1.2292
906.6	732.7	1.2256
871.4	797.6	1.2015
891	866.3	1.1786
739.2	826.3	1.1856
833.6	778.6	1.2103
715.6	779.2	1.1938
871.6	951	1.202
751.6	692.3	1.2271
1005.5	841.4	1.277
681.2	857.3	1.265
837.3	760.7	1.2684
674.7	841.2	1.2811
806.3	810.3	1.2727
860.2	1007.4	1.2611
689.8	931.3	1.2881
691.6	931.2	1.3213
682.6	855.8	1.2999
800.1	858.4	1.3074
1023.7	925.9	1.3242
733.5	930.7	1.3516
875.3	1037.6	1.3511
770.2	979.2	1.3419
1005.7	942.6	1.3716
982.3	843.9	1.3622
742.9	854.3	1.3896
974.2	1029.8	1.4227
822.3	944	1.4684
773.2	856.4	1.457
750.9	1059.4	1.4718
708	959.3	1.4748
690	941.5	1.5527
652.8	1026.4	1.575
620.7	921.3	1.5557
461.9	968	1.5553




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23397&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]1 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=23397&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23397&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132







Summary of Dendrogram
LabelHeight
11.80308131818846
22.05212524227931
34.52799693573216
45.92105660841032
58.79268928656069
69.8185316667005
79.9910315908819
810.1918747838658
910.3157453228864
1012.1100406341185
1114.8409613735095
1218.2784948945475
1319.7218693029680
1420.1303819108781
1520.5513785891066
1621.3795120252344
1723.3344650472215
1824.2393918655151
1924.5538641920167
2024.8181836264885
2127.7686227532084
2227.802949835584
2327.8863816982830
2430.3792385743948
2530.4155678660795
2631.9278600072100
2733.764746408051
2835.4005647875149
2935.8870233745505
3037.4174597019281
3141.3437634238151
3244.01603807716
3344.6602794432746
3447.5429747585277
3548.9535965371186
3649.7182801158495
3750.2070545339706
3854.7592854878775
3959.5134700365525
4060.8907419738382
4161.0218606657251
4274.016548446279
4375.7861385306848
4477.9283937768267
4582.8549314494033
4687.8180575656813
4788.2393290723047
4895.2330884341146
4998.561072181484
50103.501790565381
51115.524038508644
52126.147513111894
53138.056464791623
54143.278451044256
55145.233031943145
56177.722292245907
57190.882783709237
58205.582793136877
59239.124297653393
60310.344565226991

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 1.80308131818846 \tabularnewline
2 & 2.05212524227931 \tabularnewline
3 & 4.52799693573216 \tabularnewline
4 & 5.92105660841032 \tabularnewline
5 & 8.79268928656069 \tabularnewline
6 & 9.8185316667005 \tabularnewline
7 & 9.9910315908819 \tabularnewline
8 & 10.1918747838658 \tabularnewline
9 & 10.3157453228864 \tabularnewline
10 & 12.1100406341185 \tabularnewline
11 & 14.8409613735095 \tabularnewline
12 & 18.2784948945475 \tabularnewline
13 & 19.7218693029680 \tabularnewline
14 & 20.1303819108781 \tabularnewline
15 & 20.5513785891066 \tabularnewline
16 & 21.3795120252344 \tabularnewline
17 & 23.3344650472215 \tabularnewline
18 & 24.2393918655151 \tabularnewline
19 & 24.5538641920167 \tabularnewline
20 & 24.8181836264885 \tabularnewline
21 & 27.7686227532084 \tabularnewline
22 & 27.802949835584 \tabularnewline
23 & 27.8863816982830 \tabularnewline
24 & 30.3792385743948 \tabularnewline
25 & 30.4155678660795 \tabularnewline
26 & 31.9278600072100 \tabularnewline
27 & 33.764746408051 \tabularnewline
28 & 35.4005647875149 \tabularnewline
29 & 35.8870233745505 \tabularnewline
30 & 37.4174597019281 \tabularnewline
31 & 41.3437634238151 \tabularnewline
32 & 44.01603807716 \tabularnewline
33 & 44.6602794432746 \tabularnewline
34 & 47.5429747585277 \tabularnewline
35 & 48.9535965371186 \tabularnewline
36 & 49.7182801158495 \tabularnewline
37 & 50.2070545339706 \tabularnewline
38 & 54.7592854878775 \tabularnewline
39 & 59.5134700365525 \tabularnewline
40 & 60.8907419738382 \tabularnewline
41 & 61.0218606657251 \tabularnewline
42 & 74.016548446279 \tabularnewline
43 & 75.7861385306848 \tabularnewline
44 & 77.9283937768267 \tabularnewline
45 & 82.8549314494033 \tabularnewline
46 & 87.8180575656813 \tabularnewline
47 & 88.2393290723047 \tabularnewline
48 & 95.2330884341146 \tabularnewline
49 & 98.561072181484 \tabularnewline
50 & 103.501790565381 \tabularnewline
51 & 115.524038508644 \tabularnewline
52 & 126.147513111894 \tabularnewline
53 & 138.056464791623 \tabularnewline
54 & 143.278451044256 \tabularnewline
55 & 145.233031943145 \tabularnewline
56 & 177.722292245907 \tabularnewline
57 & 190.882783709237 \tabularnewline
58 & 205.582793136877 \tabularnewline
59 & 239.124297653393 \tabularnewline
60 & 310.344565226991 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23397&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]1.80308131818846[/C][/ROW]
[ROW][C]2[/C][C]2.05212524227931[/C][/ROW]
[ROW][C]3[/C][C]4.52799693573216[/C][/ROW]
[ROW][C]4[/C][C]5.92105660841032[/C][/ROW]
[ROW][C]5[/C][C]8.79268928656069[/C][/ROW]
[ROW][C]6[/C][C]9.8185316667005[/C][/ROW]
[ROW][C]7[/C][C]9.9910315908819[/C][/ROW]
[ROW][C]8[/C][C]10.1918747838658[/C][/ROW]
[ROW][C]9[/C][C]10.3157453228864[/C][/ROW]
[ROW][C]10[/C][C]12.1100406341185[/C][/ROW]
[ROW][C]11[/C][C]14.8409613735095[/C][/ROW]
[ROW][C]12[/C][C]18.2784948945475[/C][/ROW]
[ROW][C]13[/C][C]19.7218693029680[/C][/ROW]
[ROW][C]14[/C][C]20.1303819108781[/C][/ROW]
[ROW][C]15[/C][C]20.5513785891066[/C][/ROW]
[ROW][C]16[/C][C]21.3795120252344[/C][/ROW]
[ROW][C]17[/C][C]23.3344650472215[/C][/ROW]
[ROW][C]18[/C][C]24.2393918655151[/C][/ROW]
[ROW][C]19[/C][C]24.5538641920167[/C][/ROW]
[ROW][C]20[/C][C]24.8181836264885[/C][/ROW]
[ROW][C]21[/C][C]27.7686227532084[/C][/ROW]
[ROW][C]22[/C][C]27.802949835584[/C][/ROW]
[ROW][C]23[/C][C]27.8863816982830[/C][/ROW]
[ROW][C]24[/C][C]30.3792385743948[/C][/ROW]
[ROW][C]25[/C][C]30.4155678660795[/C][/ROW]
[ROW][C]26[/C][C]31.9278600072100[/C][/ROW]
[ROW][C]27[/C][C]33.764746408051[/C][/ROW]
[ROW][C]28[/C][C]35.4005647875149[/C][/ROW]
[ROW][C]29[/C][C]35.8870233745505[/C][/ROW]
[ROW][C]30[/C][C]37.4174597019281[/C][/ROW]
[ROW][C]31[/C][C]41.3437634238151[/C][/ROW]
[ROW][C]32[/C][C]44.01603807716[/C][/ROW]
[ROW][C]33[/C][C]44.6602794432746[/C][/ROW]
[ROW][C]34[/C][C]47.5429747585277[/C][/ROW]
[ROW][C]35[/C][C]48.9535965371186[/C][/ROW]
[ROW][C]36[/C][C]49.7182801158495[/C][/ROW]
[ROW][C]37[/C][C]50.2070545339706[/C][/ROW]
[ROW][C]38[/C][C]54.7592854878775[/C][/ROW]
[ROW][C]39[/C][C]59.5134700365525[/C][/ROW]
[ROW][C]40[/C][C]60.8907419738382[/C][/ROW]
[ROW][C]41[/C][C]61.0218606657251[/C][/ROW]
[ROW][C]42[/C][C]74.016548446279[/C][/ROW]
[ROW][C]43[/C][C]75.7861385306848[/C][/ROW]
[ROW][C]44[/C][C]77.9283937768267[/C][/ROW]
[ROW][C]45[/C][C]82.8549314494033[/C][/ROW]
[ROW][C]46[/C][C]87.8180575656813[/C][/ROW]
[ROW][C]47[/C][C]88.2393290723047[/C][/ROW]
[ROW][C]48[/C][C]95.2330884341146[/C][/ROW]
[ROW][C]49[/C][C]98.561072181484[/C][/ROW]
[ROW][C]50[/C][C]103.501790565381[/C][/ROW]
[ROW][C]51[/C][C]115.524038508644[/C][/ROW]
[ROW][C]52[/C][C]126.147513111894[/C][/ROW]
[ROW][C]53[/C][C]138.056464791623[/C][/ROW]
[ROW][C]54[/C][C]143.278451044256[/C][/ROW]
[ROW][C]55[/C][C]145.233031943145[/C][/ROW]
[ROW][C]56[/C][C]177.722292245907[/C][/ROW]
[ROW][C]57[/C][C]190.882783709237[/C][/ROW]
[ROW][C]58[/C][C]205.582793136877[/C][/ROW]
[ROW][C]59[/C][C]239.124297653393[/C][/ROW]
[ROW][C]60[/C][C]310.344565226991[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23397&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23397&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
11.80308131818846
22.05212524227931
34.52799693573216
45.92105660841032
58.79268928656069
69.8185316667005
79.9910315908819
810.1918747838658
910.3157453228864
1012.1100406341185
1114.8409613735095
1218.2784948945475
1319.7218693029680
1420.1303819108781
1520.5513785891066
1621.3795120252344
1723.3344650472215
1824.2393918655151
1924.5538641920167
2024.8181836264885
2127.7686227532084
2227.802949835584
2327.8863816982830
2430.3792385743948
2530.4155678660795
2631.9278600072100
2733.764746408051
2835.4005647875149
2935.8870233745505
3037.4174597019281
3141.3437634238151
3244.01603807716
3344.6602794432746
3447.5429747585277
3548.9535965371186
3649.7182801158495
3750.2070545339706
3854.7592854878775
3959.5134700365525
4060.8907419738382
4161.0218606657251
4274.016548446279
4375.7861385306848
4477.9283937768267
4582.8549314494033
4687.8180575656813
4788.2393290723047
4895.2330884341146
4998.561072181484
50103.501790565381
51115.524038508644
52126.147513111894
53138.056464791623
54143.278451044256
55145.233031943145
56177.722292245907
57190.882783709237
58205.582793136877
59239.124297653393
60310.344565226991



Parameters (Session):
par1 = average ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
Parameters (R input):
par1 = average ; 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')
}