## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationSat, 18 Jan 2020 20:21:07 +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/2020/Jan/18/t15793753414ob3fweyy20gbvc.htm/, Retrieved Sun, 09 May 2021 01:35:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=318987, Retrieved Sun, 09 May 2021 01:35:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact50
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Hierarchical Clustering] [] [2020-01-18 19:21:07] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
     4 ->     11 (0.471)      8 (0.164)     10 (0.030)     12 (0.022)
5 ->      6 (0.456)     12 (0.000)      7 (0.000)      8 (0.000)
2 ->      3 (0.408)      4 (0.234)     11 (0.198)     10 (0.150)
3 ->      4 (0.385)     11 (0.275)     10 (0.104)      8 (0.098)
7 ->      8 (0.302)      9 (0.039)     12 (0.000)     11 (0.000)
1 ->      2 (0.309)     10 (0.087)     12 (0.056)     11 (0.049)
8 ->     11 (0.224)      9 (0.094)     10 (0.071)     12 (0.000)
10 ->     11 (0.075)     12 (0.031)
9 ->     10 (0.051)     11 (0.000)     12 (0.000)
11 ->     12 (0.024)
6 ->     12 (0.000)      7 (0.000)      9 (0.000)      8 (0.000)


 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 0 seconds R Server Big 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=318987&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=318987&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=318987&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 Output view raw output of R engine Computing time 0 seconds R Server Big Analytics Cloud Computing Center

Parameters (Session):
par1 = complete ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
Parameters (R input):
par1 = complete ; 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 = xlabxlab = ylabylab = 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 <- NULLfor(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])-1for (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 <- par2-1for (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')}