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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 computationThu, 11 Nov 2021 11:44:24 +0100
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/Nov/11/t16366275133ofppxpd3g2mst0.htm/, Retrieved Thu, 09 May 2024 22:19:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319554, Retrieved Thu, 09 May 2024 22:19:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Hierarchical Clustering] [] [2021-11-11 10:44:24] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
	IHRc	TrGov	TrPHS	HRF	GovI1	GovI2	GovI3	Test	MobR1	MobR2
AUT	71.44	2.71	1.92	19.2	20	76.02	-2	21	30.9	19
BGR	62	3.02	2.98	20.08	14	69.9	-14	0	29.08	8
CHE	95	2.26	2.19	18.4	21	73.6	2	25	34	26
CZE	65	3.1	2.3	19	22	73.7	-36	0	26.7	14
DEU	88.7	2.74	2.34	21.4	55	72.1	16	1	40+	62
DNK	97.3	2.69	2.05	19.7	35	72.9	1	6	40+	never
ESP	85.9	3.12	2.02	19.4	59	80.9	-1	40	14.7	43
EST	72.3	2.61	2.33	19.4	31	72.86	14	4	40+	32
FIN	92	2.63	1.97	21.2	58	66	7	1	40+	74
FRA	78.6	2.97	1.96	19.7	53	87.9	-1	46	17.68	51
GBR	93	2.86	1.84	18.5	56	73.5	3	42	37	55
HRV	77.3	3.39	2.72	19.7	27	93.2	-27	13	28.13	25
HUN	66.9	2.8	2.76	18.6	24	70.4	-5	0	30.7	14
ITA	88	2.99	2.37	23	73	81.4	1	38	20.4	39
LTU	80	2.66	2.54	19	18	78.9	1	0	35.15	24
NLD	91.2	2.56	2.12	18.8	33	75.6	11	43	37.4	25
NOR	94.7	2.37	1.83	16.8	27	69.7	-28	0	40+	never
POL	76.33	3.02	2.58	16.8	37	83	-7	0	27.36	12
ROU	65	3.21	2.58	17.8	34	80.7	-3	12	25.4	20
SRB	75.89	3.04	2.73	20	16	96.7	-11	41	26.7	11
SVK	77.3	2.86	2.46	15.1	33	74.9	-4	0	34.4	10
SVN	84.4	3.1	2.54	19.1	26	82.5	-1	0	33.1	16
SWE	93.3	2.5	1.98	20	84	0	20	60	40+	never

Tables (Output of Computation)





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=319554&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=319554&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319554&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center


Figures (Output of Computation)

Input Parameters & R Code

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')
}