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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_hierarchicalclusteringdm.wasp
Title produced by softwareHierarchical Clustering
Date of computationThu, 26 Apr 2012 08:51:44 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Apr/26/t1335444738xojgw03f4cshzb2.htm/, Retrieved Mon, 29 Apr 2024 07:31:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164894, Retrieved Mon, 29 Apr 2024 07:31:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Hierarchical Clustering] [fem,all] [2012-04-26 12:51:44] [685fae5a377cc1dc51f9f02306b751ce] [Current]
- R P     [Hierarchical Clustering] [] [2012-04-30 15:17:42] [c0a25563b5321cce5982f113c9f242b0]
- R P       [Hierarchical Clustering] [] [2012-04-30 15:19:07] [c0a25563b5321cce5982f113c9f242b0]
- RMP       [Factor Analysis] [] [2012-04-30 15:20:22] [c0a25563b5321cce5982f113c9f242b0]
- RMP       [Factor Analysis] [] [2012-04-30 15:21:49] [c0a25563b5321cce5982f113c9f242b0]
- RMP       [Data Mining] [] [2012-04-30 15:23:20] [c0a25563b5321cce5982f113c9f242b0]
- R P         [Data Mining] [] [2012-05-21 13:58:41] [74be16979710d4c4e7c6647856088456]
- RMP       [Data Mining] [] [2012-04-30 15:26:13] [c0a25563b5321cce5982f113c9f242b0]
- RMP       [Data Mining] [] [2012-04-30 15:28:20] [c0a25563b5321cce5982f113c9f242b0]
- RMP       [Data Mining] [] [2012-04-30 15:29:54] [c0a25563b5321cce5982f113c9f242b0]
- RMP       [Social Networking] [] [2012-04-30 16:07:35] [c0a25563b5321cce5982f113c9f242b0]
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Dataset

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164894&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164894&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164894&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Summary of Dendrogram
LabelHeight
A119.9749843554382
A221.7025344142107
A322.6715680975093
A422.9346898823594
A523.1134692366594
A623.7907545067406
A724.7577367711985
A824.7756815297156
A925.1396101799531
A1026.2128025715758
A1126.3885744108785
A1226.7394839142419
A1328.3922796094289
A1428.7923600977759
A1531.3256290419229
A1631.962366602182
A1738.9268458079737
A1839.753373082564
A1964.2775393737694

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
A1 & 19.9749843554382 \tabularnewline
A2 & 21.7025344142107 \tabularnewline
A3 & 22.6715680975093 \tabularnewline
A4 & 22.9346898823594 \tabularnewline
A5 & 23.1134692366594 \tabularnewline
A6 & 23.7907545067406 \tabularnewline
A7 & 24.7577367711985 \tabularnewline
A8 & 24.7756815297156 \tabularnewline
A9 & 25.1396101799531 \tabularnewline
A10 & 26.2128025715758 \tabularnewline
A11 & 26.3885744108785 \tabularnewline
A12 & 26.7394839142419 \tabularnewline
A13 & 28.3922796094289 \tabularnewline
A14 & 28.7923600977759 \tabularnewline
A15 & 31.3256290419229 \tabularnewline
A16 & 31.962366602182 \tabularnewline
A17 & 38.9268458079737 \tabularnewline
A18 & 39.753373082564 \tabularnewline
A19 & 64.2775393737694 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164894&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]A1[/C][C]19.9749843554382[/C][/ROW]
[ROW][C]A2[/C][C]21.7025344142107[/C][/ROW]
[ROW][C]A3[/C][C]22.6715680975093[/C][/ROW]
[ROW][C]A4[/C][C]22.9346898823594[/C][/ROW]
[ROW][C]A5[/C][C]23.1134692366594[/C][/ROW]
[ROW][C]A6[/C][C]23.7907545067406[/C][/ROW]
[ROW][C]A7[/C][C]24.7577367711985[/C][/ROW]
[ROW][C]A8[/C][C]24.7756815297156[/C][/ROW]
[ROW][C]A9[/C][C]25.1396101799531[/C][/ROW]
[ROW][C]A10[/C][C]26.2128025715758[/C][/ROW]
[ROW][C]A11[/C][C]26.3885744108785[/C][/ROW]
[ROW][C]A12[/C][C]26.7394839142419[/C][/ROW]
[ROW][C]A13[/C][C]28.3922796094289[/C][/ROW]
[ROW][C]A14[/C][C]28.7923600977759[/C][/ROW]
[ROW][C]A15[/C][C]31.3256290419229[/C][/ROW]
[ROW][C]A16[/C][C]31.962366602182[/C][/ROW]
[ROW][C]A17[/C][C]38.9268458079737[/C][/ROW]
[ROW][C]A18[/C][C]39.753373082564[/C][/ROW]
[ROW][C]A19[/C][C]64.2775393737694[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164894&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164894&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
A119.9749843554382
A221.7025344142107
A322.6715680975093
A422.9346898823594
A523.1134692366594
A623.7907545067406
A724.7577367711985
A824.7756815297156
A925.1396101799531
A1026.2128025715758
A1126.3885744108785
A1226.7394839142419
A1328.3922796094289
A1428.7923600977759
A1531.3256290419229
A1631.962366602182
A1738.9268458079737
A1839.753373082564
A1964.2775393737694






Summary of Cut Dendrogram
LabelHeight
114.4482274175832
219.5083648398194
323.481055870703
425.0618387587087
526.7394839142419
628.7923600977759
730.9756054295657
833.6661828215102
944.0607898246828

\begin{tabular}{lllllllll}
\hline
Summary of Cut Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 14.4482274175832 \tabularnewline
2 & 19.5083648398194 \tabularnewline
3 & 23.481055870703 \tabularnewline
4 & 25.0618387587087 \tabularnewline
5 & 26.7394839142419 \tabularnewline
6 & 28.7923600977759 \tabularnewline
7 & 30.9756054295657 \tabularnewline
8 & 33.6661828215102 \tabularnewline
9 & 44.0607898246828 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164894&T=2

[TABLE]
[ROW][C]Summary of Cut Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]14.4482274175832[/C][/ROW]
[ROW][C]2[/C][C]19.5083648398194[/C][/ROW]
[ROW][C]3[/C][C]23.481055870703[/C][/ROW]
[ROW][C]4[/C][C]25.0618387587087[/C][/ROW]
[ROW][C]5[/C][C]26.7394839142419[/C][/ROW]
[ROW][C]6[/C][C]28.7923600977759[/C][/ROW]
[ROW][C]7[/C][C]30.9756054295657[/C][/ROW]
[ROW][C]8[/C][C]33.6661828215102[/C][/ROW]
[ROW][C]9[/C][C]44.0607898246828[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164894&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164894&T=2

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 Cut Dendrogram
LabelHeight
114.4482274175832
219.5083648398194
323.481055870703
425.0618387587087
526.7394839142419
628.7923600977759
730.9756054295657
833.6661828215102
944.0607898246828


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = ward ; par2 = 10 ; par3 = TRUE ; par4 = FALSE ; par5 = female ; par6 = all ; par7 = all ; par8 = ATTLES all ; par9 = variables ;
Parameters (R input):
par1 = ward ; par2 = 10 ; par3 = TRUE ; par4 = FALSE ; par5 = female ; par6 = all ; par7 = all ; par8 = ATTLES all ; par9 = variables ;
R code (references can be found in the software module):
par9 <- 'cases'
par8 <- 'ATTLES all'
par7 <- 'all'
par6 <- 'all'
par5 <- 'female'
par4 <- 'FALSE'
par3 <- 'TRUE'
par2 <- '10'
par1 <- 'ward'
x <- as.data.frame(read.table(file='https://automated.biganalytics.eu/download/utaut.csv',sep=',',header=T))
x$U25 <- 6-x$U25
if(par5 == 'female') x <- x[x$Gender==0,]
if(par5 == 'male') x <- x[x$Gender==1,]
if(par6 == 'prep') x <- x[x$Pop==1,]
if(par6 == 'bachelor') x <- x[x$Pop==0,]
if(par7 != 'all') {
x <- x[x$Year==as.numeric(par7),]
}
cAc <- with(x,cbind( A1, A2, A3, A4, A5, A6, A7, A8, A9,A10))
cAs <- with(x,cbind(A11,A12,A13,A14,A15,A16,A17,A18,A19,A20))
cA <- cbind(cAc,cAs)
cCa <- with(x,cbind(C1,C3,C5,C7, C9,C11,C13,C15,C17,C19,C21,C23,C25,C27,C29,C31,C33,C35,C37,C39,C41,C43,C45,C47))
cCp <- with(x,cbind(C2,C4,C6,C8,C10,C12,C14,C16,C18,C20,C22,C24,C26,C28,C30,C32,C34,C36,C38,C40,C42,C44,C46,C48))
cC <- cbind(cCa,cCp)
cU <- with(x,cbind(U1,U2,U3,U4,U5,U6,U7,U8,U9,U10,U11,U12,U13,U14,U15,U16,U17,U18,U19,U20,U21,U22,U23,U24,U25,U26,U27,U28,U29,U30,U31,U32,U33))
cE <- with(x,cbind(BC,NNZFG,MRT,AFL,LPM,LPC,W,WPA))
cX <- with(x,cbind(X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15,X16,X17,X18))
if (par8=='ATTLES connected') x <- cAc
if (par8=='ATTLES separate') x <- cAs
if (par8=='ATTLES all') x <- cA
if (par8=='COLLES actuals') x <- cCa
if (par8=='COLLES preferred') x <- cCp
if (par8=='COLLES all') x <- cC
if (par8=='CSUQ') x <- cU
if (par8=='Learning Activities') x <- cE
if (par8=='Exam Items') x <- cX
ncol <- length(x[1,])
for (jjj in 1:ncol) {
x <- x[!is.na(x[,jjj]),]
}
par3 <- as.logical(par3)
par4 <- as.logical(par4)
if (par3 == TRUE){
dum = xlab
xlab = ylab
ylab = dum
}
if (par9=='variables') {
x <- t(x)
} else {
ncol <- length(x[1,])
colnames(x) <- 1:ncol
}
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')
}