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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationSun, 26 Dec 2010 20:27:24 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/26/t12933952176na9idyna32l9ta.htm/, Retrieved Mon, 06 May 2024 10:49:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115797, Retrieved Mon, 06 May 2024 10:49:00 +0000
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Original text written by user:
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User-defined keywords
Estimated Impact157
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2010-12-24 17:35:28] [2ae6beac29e6e5c076a37b2886f2a670]
-       [Kendall tau Correlation Matrix] [] [2010-12-24 19:54:38] [bfba28641a1925a39268a5d6ad3b00f2]
- R       [Kendall tau Correlation Matrix] [] [2010-12-25 11:48:24] [b2f924a86c4fbfa8afa1027f3839f526]
-   PD        [Kendall tau Correlation Matrix] [] [2010-12-26 20:27:24] [ae555db68faeb138426117ca316fbf2a] [Current]
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Dataseries X:
549		3		0		1
564		3.1		-2		1
586		2.9		-4		1
604		2.4		-4		1
601		2.4		-7		1
545		2.7		-9		1
537		2.5		-13		1
552		2.1		-8		1
563		1.9		-13		1
575		0.8		-15		1
580		0.8		-15		1
575		0.3		-15		1
558		0		-10		1
564		-0.9		-12		1
581		-1		-11		1
597		-0.7		-11		1
587		-1.7		-17		1
536		-1		-18		1
524		-0.2		-19		1.09
537		0.7		-22		1.31
536		0.6		-24		1.66
533		1.9		-24		2
528		2.1		-20		2.31
516		2.7		-25		2.75
502		3.2		-22		3.42
506		4.8		-17		3.97
518		5.5		-9		4.25
534		5.4		-11		4.25
528		5.9		-13		4.18
478		5.8		-11		4
469		5.1		-9		4
490		4.1		-7		4
493		4.4		-3		4
508		3.6		-3		4
517		3.5		-6		4
514		3.1		-4		4
510		2.9		-8		4
527		2.2		-1		4
542		1.4		-2		4
565		1.2		-2		4
555		1.3		-1		4
499		1.3		1		3.9
511		1.3		2		3.75
526		1.8		2		3.75
532		1.8		-1		3.65
549		1.8		1		3.5
561		1.7		-1		3.5
557		2.1		-8		3.39
566		2		1		3.25
588		1.7		2		3.17
620		1.9		-2		3
626		2.3		-2		2.93
620		2.4		-2		2.75
573		2.5		-2		2.64
573		2.8		-6		2.5
574		2.6		-4		2.5
580		2.2		-5		2.45
590		2.8		-2		2.25
593		2.8		-1		2.25
597		2.8		-5		2.21
595		2.3		-9		2
612		2.2		-8		2
628		3		-14		2
629		2.9		-10		2
621		2.7		-11		2
569		2.7		-11		2
567		2.3		-11		2
573		2.4		-5		2
584		2.8		-2		2
589		2.3		-3		2
591		2		-6		2
595		1.9		-6		2
594		2.3		-7		2
611		2.7		-6		2
613		1.8		-2		2
611		2		-2		2
594		2.1		-4		2
543		2		0		2
537		2.4		-6		2
544		1.7		-4		2
555		1		-3		2
561		1.2		-1		2
562		1.4		-3		2
555		1.7		-6		2
547		1.8		-6		2
565		1.4		-15		2
578		1.7		-5		2
580		1.6		-11		2
569		1.4		-13		2
507		1.5		-10		2.1
501		0.9		-9		2.5
509		1.5		-11		2.5
510		1.7		-18		2.55
517		1.6		-13		2.75
519		1.2		-9		2.75
512		1.3		-8		2.85
509		1.1		-4		3.25
519		1.3		-3		3.25
523		1.2		-3		3.25
525		1.3		-3		3.25
517		1.1		-1		3.25
456		0.8		0		3.25
455		1.4		1		3.25
461		1.6		0		3.25
470		2.5		2		3.25
475		2.5		1		3.25
476		2.6		-1		3.25
471		2		-8		3.25
471		1.8		-18		3.39
503		1.9		-14		3.75
513		1.9		-4		4.03
510		2.5		0		4.49
484		2.8		4		4.5
431		3		4		4.5
436		3.1		3		4.58
443		2.9		3		4.75
448		2.2		7		4.75
460		2.5		8		4.75
467		2.7		13		4.75
460		3		15		4.75
464		3.7		14		4.75
485		3.7		14		4.7
501		4		10		4.5
521		3.5		16		4.25
488		1.7		13		4.25
439		3		15		4.11
442		2.4		13		3.75
457		2.3		12		3.51
462		2.5		13		3.37
481		2.1		11		3.21
493		0.3		9		3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=115797&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=115797&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115797&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Correlations for all pairs of data series (method=kendall)
WerkloosheidHICPConsumentenvertrouwenRente
Werkloosheid1-0.091-0.232-0.485
HICP-0.09110.1480.285
Consumentenvertrouwen-0.2320.14810.41
Rente-0.4850.2850.411

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Werkloosheid & HICP & Consumentenvertrouwen & Rente \tabularnewline
Werkloosheid & 1 & -0.091 & -0.232 & -0.485 \tabularnewline
HICP & -0.091 & 1 & 0.148 & 0.285 \tabularnewline
Consumentenvertrouwen & -0.232 & 0.148 & 1 & 0.41 \tabularnewline
Rente & -0.485 & 0.285 & 0.41 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115797&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Werkloosheid[/C][C]HICP[/C][C]Consumentenvertrouwen[/C][C]Rente[/C][/ROW]
[ROW][C]Werkloosheid[/C][C]1[/C][C]-0.091[/C][C]-0.232[/C][C]-0.485[/C][/ROW]
[ROW][C]HICP[/C][C]-0.091[/C][C]1[/C][C]0.148[/C][C]0.285[/C][/ROW]
[ROW][C]Consumentenvertrouwen[/C][C]-0.232[/C][C]0.148[/C][C]1[/C][C]0.41[/C][/ROW]
[ROW][C]Rente[/C][C]-0.485[/C][C]0.285[/C][C]0.41[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115797&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115797&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series (method=kendall)
WerkloosheidHICPConsumentenvertrouwenRente
Werkloosheid1-0.091-0.232-0.485
HICP-0.09110.1480.285
Consumentenvertrouwen-0.2320.14810.41
Rente-0.4850.2850.411







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Werkloosheid;HICP-0.2127-0.1603-0.091
p-value(0.0147)(0.0674)(0.1287)
Werkloosheid;Consumentenvertrouwen-0.3795-0.3515-0.2322
p-value(0)(0)(1e-04)
Werkloosheid;Rente-0.6708-0.691-0.4855
p-value(0)(0)(0)
HICP;Consumentenvertrouwen0.20750.210.1477
p-value(0.0174)(0.0161)(0.0151)
HICP;Rente0.49820.4120.2852
p-value(0)(0)(0)
Consumentenvertrouwen;Rente0.55030.54490.4104
p-value(0)(0)(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Werkloosheid;HICP & -0.2127 & -0.1603 & -0.091 \tabularnewline
p-value & (0.0147) & (0.0674) & (0.1287) \tabularnewline
Werkloosheid;Consumentenvertrouwen & -0.3795 & -0.3515 & -0.2322 \tabularnewline
p-value & (0) & (0) & (1e-04) \tabularnewline
Werkloosheid;Rente & -0.6708 & -0.691 & -0.4855 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
HICP;Consumentenvertrouwen & 0.2075 & 0.21 & 0.1477 \tabularnewline
p-value & (0.0174) & (0.0161) & (0.0151) \tabularnewline
HICP;Rente & 0.4982 & 0.412 & 0.2852 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Consumentenvertrouwen;Rente & 0.5503 & 0.5449 & 0.4104 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115797&T=2

[TABLE]
[ROW][C]Correlations for all pairs of data series with p-values[/C][/ROW]
[ROW][C]pair[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]Werkloosheid;HICP[/C][C]-0.2127[/C][C]-0.1603[/C][C]-0.091[/C][/ROW]
[ROW][C]p-value[/C][C](0.0147)[/C][C](0.0674)[/C][C](0.1287)[/C][/ROW]
[ROW][C]Werkloosheid;Consumentenvertrouwen[/C][C]-0.3795[/C][C]-0.3515[/C][C]-0.2322[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Werkloosheid;Rente[/C][C]-0.6708[/C][C]-0.691[/C][C]-0.4855[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]HICP;Consumentenvertrouwen[/C][C]0.2075[/C][C]0.21[/C][C]0.1477[/C][/ROW]
[ROW][C]p-value[/C][C](0.0174)[/C][C](0.0161)[/C][C](0.0151)[/C][/ROW]
[ROW][C]HICP;Rente[/C][C]0.4982[/C][C]0.412[/C][C]0.2852[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Consumentenvertrouwen;Rente[/C][C]0.5503[/C][C]0.5449[/C][C]0.4104[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115797&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115797&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Werkloosheid;HICP-0.2127-0.1603-0.091
p-value(0.0147)(0.0674)(0.1287)
Werkloosheid;Consumentenvertrouwen-0.3795-0.3515-0.2322
p-value(0)(0)(1e-04)
Werkloosheid;Rente-0.6708-0.691-0.4855
p-value(0)(0)(0)
HICP;Consumentenvertrouwen0.20750.210.1477
p-value(0.0174)(0.0161)(0.0151)
HICP;Rente0.49820.4120.2852
p-value(0)(0)(0)
Consumentenvertrouwen;Rente0.55030.54490.4104
p-value(0)(0)(0)



Parameters (Session):
par1 = kendall ;
Parameters (R input):
par1 = kendall ;
R code (references can be found in the software module):
panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
rr <- cor.test(x, y, method=par1)
r <- round(rr$p.value,2)
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep='')
if(missing(cex.cor)) cex <- 0.5/strwidth(txt)
text(0.5, 0.5, txt, cex = cex)
}
panel.hist <- function(x, ...)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
cor.test(y[1,],y[2,],method=par1)
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='')
a<-table.element(a,dum,header=TRUE)
rp <- cor.test(y[i,],y[j,],method='pearson')
a<-table.element(a,round(rp$estimate,4))
rs <- cor.test(y[i,],y[j,],method='spearman')
a<-table.element(a,round(rs$estimate,4))
rk <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,round(rk$estimate,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=T)
a<-table.element(a,paste('(',round(rp$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rs$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rk$p.value,4),')',sep=''))
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')