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 09:30:30 -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/t1226421072j2excvouax728gj.htm/, Retrieved Tue, 28 May 2024 12:27:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23687, Retrieved Tue, 28 May 2024 12:27:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Hierarchical Clustering] [Various EDA topic...] [2008-11-11 16:30:30] [db9a5fd0f9c3e1245d8075d8bb09236d] [Current]
Feedback Forum
2008-11-22 16:07:13 [Jens Peeters] [reply
Met een dendrogram, kan een reeks van clusteringen op een overzichtelijke manier weergegeven worden. Elke cluster wordt weer opgedeeld in andere clusters. Telkens gaat het om observaties die gelijkaardig kunnen worden beschouwd.
2008-11-24 10:14:52 [Stijn Van de Velde] [reply
De gelijkaardige waarnemingen worden hier per groep gesorteerd.
Om te beginnen zie je dat de data in 2 grote groepen worden opgesplitst. Daarna worden ze nog verder opgesplitst in verschillende takken.

Post a new message
Dataseries X:
9097.4	2606.3	8638.7	3219.2
12639.8	3643.8	11063.7	3552.3
13040.1	3686.4	11855.7	3787.7
11687.3	3281.6	10684.5	3392.7
11191.7	3669.3	11337.4	3550
11391.9	3191.5	10478	3681.9
11793.1	3512.7	11123.9	3519.1
13933.2	3970.7	12909.3	4283.2
12778.1	3601.2	11339.9	4046.2
11810.3	3610	10462.2	3824.9
13698.4	4172.1	12733.5	4793.1
11956.6	3956.2	10519.2	3977.7
10723.8	3142.7	10414.9	3983.4
13938.9	3884.3	12476.8	4152.9
13979.8	3892.2	12384.6	4286.1
13807.4	3613	12266.7	4348.1
12973.9	3730.5	12919.9	3949.3
12509.8	3481.3	11497.3	4166.7
12934.1	3649.5	12142	4217.9
14908.3	4215.2	13919.4	4528.2
13772.1	4066.6	12656.8	4232.2
13012.6	4196.8	12034.1	4470.9
14049.9	4536.6	13199.7	5121.2
11816.5	4441.6	10881.3	4170.8
11593.2	3548.3	11301.2	4398.6
14466.2	4735.9	13643.9	4491.4
13615.9	4130.6	12517	4251.8
14733.9	4356.2	13981.1	4901.9
13880.7	4159.6	14275.7	4745.2
13527.5	3988	13435	4666.9
13584	4167.8	13565.7	4210.4
16170.2	4902.2	16216.3	5273.6
13260.6	3909.4	12970	4095.3
14741.9	4697.6	14079.9	4610.1
15486.5	4308.9	14235	4718.1
13154.5	4420.4	12213.4	4185.5
12621.2	3544.2	12581	4314.7
15031.6	4433	14130.4	4422.6
15452.4	4479.7	14210.8	5059.2
15428	4533.2	14378.5	5043.6
13105.9	4237.5	13142.8	4436.6
14716.8	4207.4	13714.7	4922.6
14180	4394	13621.9	4454.8
16202.2	5148.4	15379.8	5058.7
14392.4	4202.2	13306.3	4768.9
15140.6	4682.5	14391.2	5171.8
15960.1	4884.3	14909.9	4989.3
14351.3	5288.9	14025.4	5202.1
13230.2	4505.2	12951.2	4838.4
15202.1	4611.5	14344.3	4876.5
17157.3	5081.1	16213.3	5845.3
16159.1	4523.1	15544.5	5686.3
13405.7	4412.8	14750.6	4753.8
17224.7	4647.4	17292.7	6620.4
17338.4	4778.6	17568.5	5597.2
17370.6	4495.3	17930.8	5643.5
18817.8	4633.5	18644.7	6357.3
16593.2	4360.5	16694.8	5909.1
17979.5	4517.9	17242.8	6165.8
17015.2	5379.9	16979.9	6321.6




Summary of computational 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 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23687&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23687&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23687&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'Gwilym Jenkins' @ 72.249.127.135







Summary of Dendrogram
LabelHeight
1167.267151586915
2178.393553695194
3220.051448529657
4306.318951421553
5313.408599116234
6343.965245337374
7354.479773753031
8371.521345281803
9409.701073955146
10428.642298426088
11447.916967751837
12457.742496802271
13463.358079674888
14470.566754273576
15470.80575612454
16492.530448668675
17510.876726813818
18528.807469690056
19534.104465437239
20537.974996386875
21593.791228686057
22594.96520066303
23603.828170922822
24657.831726203594
25717.871304622214
26718.150433420653
27791.407799608331
28830.043671077704
29862.060273079332
30874.915167316237
31876.111739448798
32940.887055501704
33959.634974472978
341007.75380470406
351021.71298838675
361025.47499793952
371036.04336781816
381114.69908662335
391185.65134083145
401289.49920164226
411356.64303612030
421410.00611387433
431415.72091276066
441507.03115613673
451598.64985422445
461906.27397959572
472030.09610239109
482246.91654023044
492407.74753126467
502671.10174205544
513046.10399788081
523123.29177953406
534403.61323051384
545512.86787646683
556876.18713235093
568030.16344700988
5722975.0320203662
5834128.9252148624
5975914.9324558848

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 167.267151586915 \tabularnewline
2 & 178.393553695194 \tabularnewline
3 & 220.051448529657 \tabularnewline
4 & 306.318951421553 \tabularnewline
5 & 313.408599116234 \tabularnewline
6 & 343.965245337374 \tabularnewline
7 & 354.479773753031 \tabularnewline
8 & 371.521345281803 \tabularnewline
9 & 409.701073955146 \tabularnewline
10 & 428.642298426088 \tabularnewline
11 & 447.916967751837 \tabularnewline
12 & 457.742496802271 \tabularnewline
13 & 463.358079674888 \tabularnewline
14 & 470.566754273576 \tabularnewline
15 & 470.80575612454 \tabularnewline
16 & 492.530448668675 \tabularnewline
17 & 510.876726813818 \tabularnewline
18 & 528.807469690056 \tabularnewline
19 & 534.104465437239 \tabularnewline
20 & 537.974996386875 \tabularnewline
21 & 593.791228686057 \tabularnewline
22 & 594.96520066303 \tabularnewline
23 & 603.828170922822 \tabularnewline
24 & 657.831726203594 \tabularnewline
25 & 717.871304622214 \tabularnewline
26 & 718.150433420653 \tabularnewline
27 & 791.407799608331 \tabularnewline
28 & 830.043671077704 \tabularnewline
29 & 862.060273079332 \tabularnewline
30 & 874.915167316237 \tabularnewline
31 & 876.111739448798 \tabularnewline
32 & 940.887055501704 \tabularnewline
33 & 959.634974472978 \tabularnewline
34 & 1007.75380470406 \tabularnewline
35 & 1021.71298838675 \tabularnewline
36 & 1025.47499793952 \tabularnewline
37 & 1036.04336781816 \tabularnewline
38 & 1114.69908662335 \tabularnewline
39 & 1185.65134083145 \tabularnewline
40 & 1289.49920164226 \tabularnewline
41 & 1356.64303612030 \tabularnewline
42 & 1410.00611387433 \tabularnewline
43 & 1415.72091276066 \tabularnewline
44 & 1507.03115613673 \tabularnewline
45 & 1598.64985422445 \tabularnewline
46 & 1906.27397959572 \tabularnewline
47 & 2030.09610239109 \tabularnewline
48 & 2246.91654023044 \tabularnewline
49 & 2407.74753126467 \tabularnewline
50 & 2671.10174205544 \tabularnewline
51 & 3046.10399788081 \tabularnewline
52 & 3123.29177953406 \tabularnewline
53 & 4403.61323051384 \tabularnewline
54 & 5512.86787646683 \tabularnewline
55 & 6876.18713235093 \tabularnewline
56 & 8030.16344700988 \tabularnewline
57 & 22975.0320203662 \tabularnewline
58 & 34128.9252148624 \tabularnewline
59 & 75914.9324558848 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23687&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]167.267151586915[/C][/ROW]
[ROW][C]2[/C][C]178.393553695194[/C][/ROW]
[ROW][C]3[/C][C]220.051448529657[/C][/ROW]
[ROW][C]4[/C][C]306.318951421553[/C][/ROW]
[ROW][C]5[/C][C]313.408599116234[/C][/ROW]
[ROW][C]6[/C][C]343.965245337374[/C][/ROW]
[ROW][C]7[/C][C]354.479773753031[/C][/ROW]
[ROW][C]8[/C][C]371.521345281803[/C][/ROW]
[ROW][C]9[/C][C]409.701073955146[/C][/ROW]
[ROW][C]10[/C][C]428.642298426088[/C][/ROW]
[ROW][C]11[/C][C]447.916967751837[/C][/ROW]
[ROW][C]12[/C][C]457.742496802271[/C][/ROW]
[ROW][C]13[/C][C]463.358079674888[/C][/ROW]
[ROW][C]14[/C][C]470.566754273576[/C][/ROW]
[ROW][C]15[/C][C]470.80575612454[/C][/ROW]
[ROW][C]16[/C][C]492.530448668675[/C][/ROW]
[ROW][C]17[/C][C]510.876726813818[/C][/ROW]
[ROW][C]18[/C][C]528.807469690056[/C][/ROW]
[ROW][C]19[/C][C]534.104465437239[/C][/ROW]
[ROW][C]20[/C][C]537.974996386875[/C][/ROW]
[ROW][C]21[/C][C]593.791228686057[/C][/ROW]
[ROW][C]22[/C][C]594.96520066303[/C][/ROW]
[ROW][C]23[/C][C]603.828170922822[/C][/ROW]
[ROW][C]24[/C][C]657.831726203594[/C][/ROW]
[ROW][C]25[/C][C]717.871304622214[/C][/ROW]
[ROW][C]26[/C][C]718.150433420653[/C][/ROW]
[ROW][C]27[/C][C]791.407799608331[/C][/ROW]
[ROW][C]28[/C][C]830.043671077704[/C][/ROW]
[ROW][C]29[/C][C]862.060273079332[/C][/ROW]
[ROW][C]30[/C][C]874.915167316237[/C][/ROW]
[ROW][C]31[/C][C]876.111739448798[/C][/ROW]
[ROW][C]32[/C][C]940.887055501704[/C][/ROW]
[ROW][C]33[/C][C]959.634974472978[/C][/ROW]
[ROW][C]34[/C][C]1007.75380470406[/C][/ROW]
[ROW][C]35[/C][C]1021.71298838675[/C][/ROW]
[ROW][C]36[/C][C]1025.47499793952[/C][/ROW]
[ROW][C]37[/C][C]1036.04336781816[/C][/ROW]
[ROW][C]38[/C][C]1114.69908662335[/C][/ROW]
[ROW][C]39[/C][C]1185.65134083145[/C][/ROW]
[ROW][C]40[/C][C]1289.49920164226[/C][/ROW]
[ROW][C]41[/C][C]1356.64303612030[/C][/ROW]
[ROW][C]42[/C][C]1410.00611387433[/C][/ROW]
[ROW][C]43[/C][C]1415.72091276066[/C][/ROW]
[ROW][C]44[/C][C]1507.03115613673[/C][/ROW]
[ROW][C]45[/C][C]1598.64985422445[/C][/ROW]
[ROW][C]46[/C][C]1906.27397959572[/C][/ROW]
[ROW][C]47[/C][C]2030.09610239109[/C][/ROW]
[ROW][C]48[/C][C]2246.91654023044[/C][/ROW]
[ROW][C]49[/C][C]2407.74753126467[/C][/ROW]
[ROW][C]50[/C][C]2671.10174205544[/C][/ROW]
[ROW][C]51[/C][C]3046.10399788081[/C][/ROW]
[ROW][C]52[/C][C]3123.29177953406[/C][/ROW]
[ROW][C]53[/C][C]4403.61323051384[/C][/ROW]
[ROW][C]54[/C][C]5512.86787646683[/C][/ROW]
[ROW][C]55[/C][C]6876.18713235093[/C][/ROW]
[ROW][C]56[/C][C]8030.16344700988[/C][/ROW]
[ROW][C]57[/C][C]22975.0320203662[/C][/ROW]
[ROW][C]58[/C][C]34128.9252148624[/C][/ROW]
[ROW][C]59[/C][C]75914.9324558848[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23687&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23687&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
1167.267151586915
2178.393553695194
3220.051448529657
4306.318951421553
5313.408599116234
6343.965245337374
7354.479773753031
8371.521345281803
9409.701073955146
10428.642298426088
11447.916967751837
12457.742496802271
13463.358079674888
14470.566754273576
15470.80575612454
16492.530448668675
17510.876726813818
18528.807469690056
19534.104465437239
20537.974996386875
21593.791228686057
22594.96520066303
23603.828170922822
24657.831726203594
25717.871304622214
26718.150433420653
27791.407799608331
28830.043671077704
29862.060273079332
30874.915167316237
31876.111739448798
32940.887055501704
33959.634974472978
341007.75380470406
351021.71298838675
361025.47499793952
371036.04336781816
381114.69908662335
391185.65134083145
401289.49920164226
411356.64303612030
421410.00611387433
431415.72091276066
441507.03115613673
451598.64985422445
461906.27397959572
472030.09610239109
482246.91654023044
492407.74753126467
502671.10174205544
513046.10399788081
523123.29177953406
534403.61323051384
545512.86787646683
556876.18713235093
568030.16344700988
5722975.0320203662
5834128.9252148624
5975914.9324558848



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')
}