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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 computationWed, 12 Nov 2008 07:05:44 -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/12/t1226498806dcmydsff56swe0t.htm/, Retrieved Sun, 19 May 2024 10:08:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24197, Retrieved Sun, 19 May 2024 10:08:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Testing Mean with known Variance - Type II Error] [] [2008-11-12 10:52:51] [d9be4962be2d3234142c279ef29acbcf]
F RMPD    [Hierarchical Clustering] [] [2008-11-12 14:05:44] [8767719db498704e1fee27044c098ad0] [Current]
Feedback Forum
2008-11-17 13:41:07 [Stef Vermeiren] [reply] 
Wat de student zegt is wel juist, maar er kan ook nog gezegd worden dat men de tijdreeks zal opdelen in 2 subcategoriën (deze worden dan op hun beurt weer opgedeeld waardoor de eigenschappen steeds geconcentreerder worden en dus meer gelijkaardig). De gegevens die zich in 1 cluster bevinden bevatten gelijkaardige eigenschappen.
2008-11-20 13:55:33 [6066575aa30c0611e452e930b1dff53d] [reply] 
hier had men ook nog kunnen vermelden dat de computer de tijdreeks gaat opsplitsen in 2 delen. Bovendien bevinden de lagere en hogere periodes zich zowel aan de linkerkant als aan de rechterkant. Er is dus geen duidelijke lijn in te trekken.
2008-11-20 16:23:59 [Gert-Jan Geudens] [reply] 
Ik ga niet akkoord met de conclusie van de student(e). Een dendrogram heeft als doel de gelijkaardige data, te groeperen in clusters. Uit de dendrogram van de student kunnen we duidelijk opmerken dat de maanden 25,22,48,13,1,33,10,54,56,50,36,60,45,38,49,42,61,46,34,58,9,6,8,37,31,32,20,19,7,24,43,12 zich in de linkse cluster bevinden. De gegevens van deze maanden zijn dus met andere woorden gelijk aan elkaar. De resterende maanden bevinden zich in de rechtercluster en zijn dus ook ongeveer gelijk aan elkaar.
2008-11-24 19:50:29 [4679c4d03f1d346a85e79d87ba60ec2b] [reply] 
Op zich wordt er enkel gezegd wat een dendrogram kan doen maar er wordt niets gezegd over mogelijke patronen die de student hier mogelijk uit zou kunnen halen.Er wordt geen echte conclusie getrokken hier. Er kan o.a. gezegd worden dat hier de gegevens kunnen onderverdeeld worden in 2 subgroepen.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
16	14	24
8	-7	-6
-10	-13	-17
-24	-11	-44
-19	-9	-36
8	8	4
24	24	29
14	4	8
7	7	3
9	16	8
-26	-30	-49
19	26	32
15	19	25
-1	2	-1
-10	-12	-20
-21	-29	-34
-14	-24	-31
-27	-16	-12
26	25	25
23	22	25
5	-7	7
19	17	13
-19	-29	-40
24	18	32
17	15	14
1	1	-5
-9	6	-14
-16	-21	-42
-21	-23	-24
-14	-15	-11
31	24	20
27	15	7
10	15	12
12	14	4
-23	-25	-37
13	14	19
26	21	16
-1	13	2
4	4	-9
-16	-16	-36
-5	13	-29
9	20	3
23	27	33
9	-8	9
2	13	13
10	12	3
-29	-25	-47
17	20	18
9	22	7
9	16	16
-10	-12	-12
-23	-13	-23
13	7	-18
13	12	11
-9	-8	-4
9	12	17
5	-13	-4
8	12	-1
-18	-25	-41
7	0	26
4	18	3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24197&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24197&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24197&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 computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Summary of Dendrogram
LabelHeight
11.73205080756888
23
33
43.16227766016838
54.12310562561766
64.24264068711928
74.24264068711928
84.24264068711928
94.24264068711928
104.47213595499958
114.58257569495584
124.58257569495584
134.69588736423469
145.09901951359278
155.19615242270663
165.3851648071345
175.48172765326135
185.76046855827592
196.16441400296898
206.4535599249993
217
227.07106781186548
237.13262084327031
247.37835882693455
257.49081315919221
267.61577310586391
278.78887653890689
289.9498743710662
2910.2312416249102
3010.8468451912246
3111.3083336271833
3211.4017542509914
3311.9112311450360
3412.0830459735946
3512.1367207232760
3613.1038723559249
3713.6651476105399
3813.7194335193147
3915.7578353437117
4016.3170691166258
4117.0293863659264
4217.3389407039620
4317.7159228541959
4421.9234741874105
4522.0141990079642
4623.8278459936162
4725.1114628651686
4826.0093030634111
4928.8107034727402
5029.5625962444557
5132.9367756335492
5238.2704933646133
5341.2117988278412
5456.8306799024852
5557.9446486426321
5677.0245219960672
5778.1775092566134
58161.284195547647
59328.024290680700
60962.535344175549

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 1.73205080756888 \tabularnewline
2 & 3 \tabularnewline
3 & 3 \tabularnewline
4 & 3.16227766016838 \tabularnewline
5 & 4.12310562561766 \tabularnewline
6 & 4.24264068711928 \tabularnewline
7 & 4.24264068711928 \tabularnewline
8 & 4.24264068711928 \tabularnewline
9 & 4.24264068711928 \tabularnewline
10 & 4.47213595499958 \tabularnewline
11 & 4.58257569495584 \tabularnewline
12 & 4.58257569495584 \tabularnewline
13 & 4.69588736423469 \tabularnewline
14 & 5.09901951359278 \tabularnewline
15 & 5.19615242270663 \tabularnewline
16 & 5.3851648071345 \tabularnewline
17 & 5.48172765326135 \tabularnewline
18 & 5.76046855827592 \tabularnewline
19 & 6.16441400296898 \tabularnewline
20 & 6.4535599249993 \tabularnewline
21 & 7 \tabularnewline
22 & 7.07106781186548 \tabularnewline
23 & 7.13262084327031 \tabularnewline
24 & 7.37835882693455 \tabularnewline
25 & 7.49081315919221 \tabularnewline
26 & 7.61577310586391 \tabularnewline
27 & 8.78887653890689 \tabularnewline
28 & 9.9498743710662 \tabularnewline
29 & 10.2312416249102 \tabularnewline
30 & 10.8468451912246 \tabularnewline
31 & 11.3083336271833 \tabularnewline
32 & 11.4017542509914 \tabularnewline
33 & 11.9112311450360 \tabularnewline
34 & 12.0830459735946 \tabularnewline
35 & 12.1367207232760 \tabularnewline
36 & 13.1038723559249 \tabularnewline
37 & 13.6651476105399 \tabularnewline
38 & 13.7194335193147 \tabularnewline
39 & 15.7578353437117 \tabularnewline
40 & 16.3170691166258 \tabularnewline
41 & 17.0293863659264 \tabularnewline
42 & 17.3389407039620 \tabularnewline
43 & 17.7159228541959 \tabularnewline
44 & 21.9234741874105 \tabularnewline
45 & 22.0141990079642 \tabularnewline
46 & 23.8278459936162 \tabularnewline
47 & 25.1114628651686 \tabularnewline
48 & 26.0093030634111 \tabularnewline
49 & 28.8107034727402 \tabularnewline
50 & 29.5625962444557 \tabularnewline
51 & 32.9367756335492 \tabularnewline
52 & 38.2704933646133 \tabularnewline
53 & 41.2117988278412 \tabularnewline
54 & 56.8306799024852 \tabularnewline
55 & 57.9446486426321 \tabularnewline
56 & 77.0245219960672 \tabularnewline
57 & 78.1775092566134 \tabularnewline
58 & 161.284195547647 \tabularnewline
59 & 328.024290680700 \tabularnewline
60 & 962.535344175549 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24197&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]1.73205080756888[/C][/ROW]
[ROW][C]2[/C][C]3[/C][/ROW]
[ROW][C]3[/C][C]3[/C][/ROW]
[ROW][C]4[/C][C]3.16227766016838[/C][/ROW]
[ROW][C]5[/C][C]4.12310562561766[/C][/ROW]
[ROW][C]6[/C][C]4.24264068711928[/C][/ROW]
[ROW][C]7[/C][C]4.24264068711928[/C][/ROW]
[ROW][C]8[/C][C]4.24264068711928[/C][/ROW]
[ROW][C]9[/C][C]4.24264068711928[/C][/ROW]
[ROW][C]10[/C][C]4.47213595499958[/C][/ROW]
[ROW][C]11[/C][C]4.58257569495584[/C][/ROW]
[ROW][C]12[/C][C]4.58257569495584[/C][/ROW]
[ROW][C]13[/C][C]4.69588736423469[/C][/ROW]
[ROW][C]14[/C][C]5.09901951359278[/C][/ROW]
[ROW][C]15[/C][C]5.19615242270663[/C][/ROW]
[ROW][C]16[/C][C]5.3851648071345[/C][/ROW]
[ROW][C]17[/C][C]5.48172765326135[/C][/ROW]
[ROW][C]18[/C][C]5.76046855827592[/C][/ROW]
[ROW][C]19[/C][C]6.16441400296898[/C][/ROW]
[ROW][C]20[/C][C]6.4535599249993[/C][/ROW]
[ROW][C]21[/C][C]7[/C][/ROW]
[ROW][C]22[/C][C]7.07106781186548[/C][/ROW]
[ROW][C]23[/C][C]7.13262084327031[/C][/ROW]
[ROW][C]24[/C][C]7.37835882693455[/C][/ROW]
[ROW][C]25[/C][C]7.49081315919221[/C][/ROW]
[ROW][C]26[/C][C]7.61577310586391[/C][/ROW]
[ROW][C]27[/C][C]8.78887653890689[/C][/ROW]
[ROW][C]28[/C][C]9.9498743710662[/C][/ROW]
[ROW][C]29[/C][C]10.2312416249102[/C][/ROW]
[ROW][C]30[/C][C]10.8468451912246[/C][/ROW]
[ROW][C]31[/C][C]11.3083336271833[/C][/ROW]
[ROW][C]32[/C][C]11.4017542509914[/C][/ROW]
[ROW][C]33[/C][C]11.9112311450360[/C][/ROW]
[ROW][C]34[/C][C]12.0830459735946[/C][/ROW]
[ROW][C]35[/C][C]12.1367207232760[/C][/ROW]
[ROW][C]36[/C][C]13.1038723559249[/C][/ROW]
[ROW][C]37[/C][C]13.6651476105399[/C][/ROW]
[ROW][C]38[/C][C]13.7194335193147[/C][/ROW]
[ROW][C]39[/C][C]15.7578353437117[/C][/ROW]
[ROW][C]40[/C][C]16.3170691166258[/C][/ROW]
[ROW][C]41[/C][C]17.0293863659264[/C][/ROW]
[ROW][C]42[/C][C]17.3389407039620[/C][/ROW]
[ROW][C]43[/C][C]17.7159228541959[/C][/ROW]
[ROW][C]44[/C][C]21.9234741874105[/C][/ROW]
[ROW][C]45[/C][C]22.0141990079642[/C][/ROW]
[ROW][C]46[/C][C]23.8278459936162[/C][/ROW]
[ROW][C]47[/C][C]25.1114628651686[/C][/ROW]
[ROW][C]48[/C][C]26.0093030634111[/C][/ROW]
[ROW][C]49[/C][C]28.8107034727402[/C][/ROW]
[ROW][C]50[/C][C]29.5625962444557[/C][/ROW]
[ROW][C]51[/C][C]32.9367756335492[/C][/ROW]
[ROW][C]52[/C][C]38.2704933646133[/C][/ROW]
[ROW][C]53[/C][C]41.2117988278412[/C][/ROW]
[ROW][C]54[/C][C]56.8306799024852[/C][/ROW]
[ROW][C]55[/C][C]57.9446486426321[/C][/ROW]
[ROW][C]56[/C][C]77.0245219960672[/C][/ROW]
[ROW][C]57[/C][C]78.1775092566134[/C][/ROW]
[ROW][C]58[/C][C]161.284195547647[/C][/ROW]
[ROW][C]59[/C][C]328.024290680700[/C][/ROW]
[ROW][C]60[/C][C]962.535344175549[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24197&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24197&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
11.73205080756888
23
33
43.16227766016838
54.12310562561766
64.24264068711928
74.24264068711928
84.24264068711928
94.24264068711928
104.47213595499958
114.58257569495584
124.58257569495584
134.69588736423469
145.09901951359278
155.19615242270663
165.3851648071345
175.48172765326135
185.76046855827592
196.16441400296898
206.4535599249993
217
227.07106781186548
237.13262084327031
247.37835882693455
257.49081315919221
267.61577310586391
278.78887653890689
289.9498743710662
2910.2312416249102
3010.8468451912246
3111.3083336271833
3211.4017542509914
3311.9112311450360
3412.0830459735946
3512.1367207232760
3613.1038723559249
3713.6651476105399
3813.7194335193147
3915.7578353437117
4016.3170691166258
4117.0293863659264
4217.3389407039620
4317.7159228541959
4421.9234741874105
4522.0141990079642
4623.8278459936162
4725.1114628651686
4826.0093030634111
4928.8107034727402
5029.5625962444557
5132.9367756335492
5238.2704933646133
5341.2117988278412
5456.8306799024852
5557.9446486426321
5677.0245219960672
5778.1775092566134
58161.284195547647
59328.024290680700
60962.535344175549


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')
}