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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 computationTue, 14 Dec 2010 19:07:17 +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/14/t1292353529994pm8cvydhz9b9.htm/, Retrieved Thu, 02 May 2024 21:08:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110045, Retrieved Thu, 02 May 2024 21:08:32 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2010-12-12 09:56:12] [c1605865773cc027e55b238d879a644c]
-         [Kendall tau Correlation Matrix] [WS 10 - Kendall's...] [2010-12-14 19:07:17] [85c2b01fe80f9fc86b9396d4d142e465] [Current]
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Dataseries X:
16198.9	16896.2	0
16554.2	16698	0
19554.2	19691.6	0
15903.8	15930.7	0
18003.8	17444.6	0
18329.6	17699.4	0
16260.7	15189.8	0
14851.9	15672.7	0
18174.1	17180.8	0
18406.6	17664.9	0
18466.5	17862.9	0
16016.5	16162.3	0
17428.5	17463.6	0
17167.2	16772.1	0
19630	19106.9	0
17183.6	16721.3	0
18344.7	18161.3	0
19301.4	18509.9	0
18147.5	17802.7	0
16192.9	16409.9	0
18374.4	17967.7	0
20515.2	20286.6	0
18957.2	19537.3	0
16471.5	18021.9	0
18746.8	20194.3	0
19009.5	19049.6	0
19211.2	20244.7	0
20547.7	21473.3	0
19325.8	19673.6	0
20605.5	21053.2	0
20056.9	20159.5	0
16141.4	18203.6	0
20359.8	21289.5	0
19711.6	20432.3	1
15638.6	17180.4	1
14384.5	15816.8	1
13855.6	15071.8	1
14308.3	14521.1	1
15290.6	15668.8	1
14423.8	14346.9	1
13779.7	13881	1
15686.3	15465.9	1
14733.8	14238.2	1
12522.5	13557.7	1
16189.4	16127.6	1
16059.1	16793.9	1
16007.1	16014	1
15806.8	16867.9	1
15160	16014.6	0
15692.1	15878.6	0
18908.9	18664.9	0
16969.9	17962.5	0
16997.5	17332.7	0
19858.9	19542.1	0
17681.2	17203.6	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110045&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110045&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110045&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Correlations for all pairs of data series (method=kendall)
UitvoerInvoerCrisis
Uitvoer10.786-0.513
Invoer0.7861-0.464
Crisis-0.513-0.4641

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Uitvoer & Invoer & Crisis \tabularnewline
Uitvoer & 1 & 0.786 & -0.513 \tabularnewline
Invoer & 0.786 & 1 & -0.464 \tabularnewline
Crisis & -0.513 & -0.464 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110045&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Uitvoer[/C][C]Invoer[/C][C]Crisis[/C][/ROW]
[ROW][C]Uitvoer[/C][C]1[/C][C]0.786[/C][C]-0.513[/C][/ROW]
[ROW][C]Invoer[/C][C]0.786[/C][C]1[/C][C]-0.464[/C][/ROW]
[ROW][C]Crisis[/C][C]-0.513[/C][C]-0.464[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110045&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110045&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)
UitvoerInvoerCrisis
Uitvoer10.786-0.513
Invoer0.7861-0.464
Crisis-0.513-0.4641







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Uitvoer;Invoer0.93530.93030.7859
p-value(0)(0)(0)
Uitvoer;Crisis-0.6158-0.6224-0.5128
p-value(0)(0)(0)
Invoer;Crisis-0.5457-0.5632-0.464
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
Uitvoer;Invoer & 0.9353 & 0.9303 & 0.7859 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Uitvoer;Crisis & -0.6158 & -0.6224 & -0.5128 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Invoer;Crisis & -0.5457 & -0.5632 & -0.464 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110045&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]Uitvoer;Invoer[/C][C]0.9353[/C][C]0.9303[/C][C]0.7859[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Uitvoer;Crisis[/C][C]-0.6158[/C][C]-0.6224[/C][C]-0.5128[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Invoer;Crisis[/C][C]-0.5457[/C][C]-0.5632[/C][C]-0.464[/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=110045&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110045&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
Uitvoer;Invoer0.93530.93030.7859
p-value(0)(0)(0)
Uitvoer;Crisis-0.6158-0.6224-0.5128
p-value(0)(0)(0)
Invoer;Crisis-0.5457-0.5632-0.464
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')