Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationTue, 15 Jun 2021 09:51:29 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2021/Jun/15/t1623744315r3dv39pmuin6oxi.htm/, Retrieved Fri, 19 Apr 2024 21:09:47 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Fri, 19 Apr 2024 21:09:47 +0200
QR Codes:

Original text written by user:
IsPrivate?This computation is/was private until 2022-01-01
User-defined keywordsVis mon village
Estimated Impact0
Dataseries X:
Name	Nb Projets	Village	Population	Agriculture	Paysage	Déclin	Isolement	Convivial	Habécole	Officiel	Région	Cadrevie	Evidence	Autres
Nivelles	55.0	78.2	52.7	61.8	98.2	27.3	14.5	34.5	9.1	16.4	5.5	14.5	0.0	9.1
Huy	43.0	83.7	81.4	83.7	132.6	20.9	16.3	14.0	27.9	25.6	27.9	7.0	9.3	16.3
Liège	31.0	87.1	41.9	45.2	145.2	41.9	29.0	9.7	29.0	6.5	9.7	12.9	6.5	9.7
Verviers	39.0	74.4	69.2	53.8	135.9	35.9	10.3	30.8	12.8	10.3	17.9	12.8	12.8	15.4
Waremme	25.0	76.0	68.0	84.0	156.0	12.0	4.0	36.0	20.0	20.0	64.0	8.0	4.0	24.0
Dinant	60.0	91.7	70.0	41.7	85.0	55.0	33.3	33.3	30.0	13.3	20.0	15.0	5.0	33.3
Namur	61.0	70.5	52.5	55.7	75.4	44.3	11.5	23.0	29.5	16.4	16.4	8.2	3.3	11.5
Philippeville	46.0	67.4	134.8	52.2	93.5	110.9	58.7	17.4	39.1	21.7	19.6	10.9	6.5	6.5
Arlon	6.0	116.7	100.0	16.7	516.7	16.7	16.7	16.7	0.0	16.7	0.0	100.0	0.0	0.0
Bastogne	40.0	75.0	57.5	30.0	82.5	40.0	32.5	12.5	12.5	0.0	10.0	2.5	10.0	12.5
Marche	25.0	76.0	68.0	52.0	152.0	24.0	28.0	24.0	8.0	8.0	12.0	4.0	12.0	36.0
Neufchâteau	20.0	65.0	65.0	35.0	160.0	55.0	30.0	20.0	15.0	5.0	10.0	0.0	0.0	40.0
Virton	15.0	73.3	60.0	33.3	253.3	40.0	13.3	60.0	20.0	0.0	6.7	6.7	0.0	26.7
Ath	19.0	73.7	89.5	63.2	210.5	26.3	15.8	26.3	31.6	31.6	5.3	0.0	0.0	36.8
Charleroi	18.0	77.8	72.2	66.7	233.3	33.3	50.0	11.1	50.0	0.0	22.2	16.7	11.1	11.1
La Louvière	7.0	42.9	14.3	100.0	457.1	0.0	0.0	28.6	28.6	14.3	0.0	28.6	0.0	28.6
Mons	13.0	46.2	53.8	92.3	261.5	23.1	15.4	0.0	15.4	23.1	0.0	0.0	0.0	0.0
Soignies	7.0	85.7	57.1	85.7	457.1	28.6	0.0	0.0	0.0	0.0	0.0	14.3	0.0	28.6
Thuin	20.0	60.0	80.0	45.0	180.0	75.0	25.0	10.0	55.0	25.0	5.0	10.0	0.0	20.0
Tournai	27.0	92.6	40.7	37.0	125.9	25.9	14.8	25.9	18.5	29.6	0.0	3.7	3.7	14.8




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center



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):
par4 <- 'FALSE'
par3 <- 'FALSE'
par2 <- 'ALL'
par1 <- 'ward'
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')
}