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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 computationMon, 09 Nov 2009 05:59:42 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/09/t1257771628a122mzehobnuurd.htm/, Retrieved Thu, 28 Mar 2024 17:42:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54792, Retrieved Thu, 28 Mar 2024 17:42:12 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact210
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [workshop 6] [2009-11-09 12:59:42] [6198946fb53eb5eb18db46bb758f7fde] [Current]
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Dataseries X:
0.6348	1.5291	1.4098	1.6891
0.634	1.5358	1.4027	1.7236
0.62915	1.5355	1.4167	1.8072
0.62168	1.5287	1.3903	1.7847
0.1328	1.5334	1.3473	1.6813
0.6089	1.5225	1.3016	1.6469
0.60857	1.5135	1.3153	1.689
0.62672	1.5144	1.3857	1.7169
0.62291	1.4913	1.426	1.8036
0.62393	1.4793	1.4224	1.7955
0.61838	1.4663	1.4153	1.7172
0.62012	1.4749	1.4075	1.7348
0.61659	1.4745	1.4135	1.7094
0.6116	1.4775	1.388	1.6963
0.61573	1.4678	1.3903	1.6695
0.61407	1.4658	1.4008	1.6537
0.62823	1.4572	1.421	1.6662
0.64405	1.4721	1.4627	1.6793
0.6387	1.4624	1.5321	1.7922
0.63633	1.4636	1.5333	1.8045
0.63059	1.4649	1.5434	1.7927
0.62994	1.465	1.5481	1.7831
0.63709	1.4673	1.5735	1.7847
0.64217	1.4679	1.5872	1.8076
0.65711	1.4621	1.6364	1.8218
0.66977	1.4674	1.6299	1.8112
0.68255	1.4695	1.5943	1.795
0.68902	1.4964	1.5851	1.7813
0.71322	1.5155	1.6016	1.7866
0.70224	1.5411	1.5798	1.7552
0.70045	1.5476	1.5694	1.7184
0.69919	1.54	1.557	1.7114
0.69693	1.5474	1.533	1.6967
0.69763	1.5485	1.5489	1.6867
0.69278	1.559	1.5361	1.6337
0.70196	1.5544	1.6131	1.6626
0.69215	1.5657	1.6346	1.6374
0.6769	1.5734	1.6817	1.626
0.67124	1.567	1.6314	1.637
0.66532	1.5547	1.6068	1.6142
0.67157	1.54	1.6541	1.7033
0.66428	1.5192	1.6492	1.7483
0.66576	1.527	1.622	1.7135
0.66942	1.5387	1.6007	1.7147
0.6813	1.5431	1.5767	1.7396
0.69144	1.5426	1.56	1.7049
0.69862	1.5216	1.554	1.6867
0.695	1.5364	1.6333	1.7462
0.69867	1.5469	1.606	1.7147
0.68968	1.5501	1.6128	1.667
0.69233	1.5494	1.6064	1.6806
0.68293	1.5475	1.5991	1.6738
0.68399	1.5448	1.5942	1.6571
0.66895	1.5391	1.5111	1.5875
0.68756	1.5578	1.473	1.6002
0.68527	1.5528	1.4819	1.6144
0.6776	1.5496	1.4452	1.6009
0.68137	1.549	1.4149	1.5937
0.67933	1.5449	1.3944	1.603
0.67922	1.5479	1.3778	1.5979




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=54792&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=54792&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54792&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







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( Britse_Pond , Zwitserse_Frank )0.3950268595113098.26267252551638e-06
tau( Britse_Pond , Canadese_Dollar )0.4334557957727819.98315086597756e-07
tau( Britse_Pond , Australische_Dollar )-0.08085951452494170.361716412520577
tau( Zwitserse_Frank , Canadese_Dollar )0.1910684002261160.0310971490372594
tau( Zwitserse_Frank , Australische_Dollar )-0.4649322010663811.57915250629336e-07
tau( Canadese_Dollar , Australische_Dollar )0.1052036367376480.235467885319790

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( Britse_Pond , Zwitserse_Frank ) & 0.395026859511309 & 8.26267252551638e-06 \tabularnewline
tau( Britse_Pond , Canadese_Dollar ) & 0.433455795772781 & 9.98315086597756e-07 \tabularnewline
tau( Britse_Pond , Australische_Dollar ) & -0.0808595145249417 & 0.361716412520577 \tabularnewline
tau( Zwitserse_Frank , Canadese_Dollar ) & 0.191068400226116 & 0.0310971490372594 \tabularnewline
tau( Zwitserse_Frank , Australische_Dollar ) & -0.464932201066381 & 1.57915250629336e-07 \tabularnewline
tau( Canadese_Dollar , Australische_Dollar ) & 0.105203636737648 & 0.235467885319790 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54792&T=1

[TABLE]
[ROW][C]Kendall tau rank correlations for all pairs of data series[/C][/ROW]
[ROW][C]pair[/C][C]tau[/C][C]p-value[/C][/ROW]
[ROW][C]tau( Britse_Pond , Zwitserse_Frank )[/C][C]0.395026859511309[/C][C]8.26267252551638e-06[/C][/ROW]
[ROW][C]tau( Britse_Pond , Canadese_Dollar )[/C][C]0.433455795772781[/C][C]9.98315086597756e-07[/C][/ROW]
[ROW][C]tau( Britse_Pond , Australische_Dollar )[/C][C]-0.0808595145249417[/C][C]0.361716412520577[/C][/ROW]
[ROW][C]tau( Zwitserse_Frank , Canadese_Dollar )[/C][C]0.191068400226116[/C][C]0.0310971490372594[/C][/ROW]
[ROW][C]tau( Zwitserse_Frank , Australische_Dollar )[/C][C]-0.464932201066381[/C][C]1.57915250629336e-07[/C][/ROW]
[ROW][C]tau( Canadese_Dollar , Australische_Dollar )[/C][C]0.105203636737648[/C][C]0.235467885319790[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54792&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54792&T=1

As an alternative you can also use a QR Code:  

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

Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( Britse_Pond , Zwitserse_Frank )0.3950268595113098.26267252551638e-06
tau( Britse_Pond , Canadese_Dollar )0.4334557957727819.98315086597756e-07
tau( Britse_Pond , Australische_Dollar )-0.08085951452494170.361716412520577
tau( Zwitserse_Frank , Canadese_Dollar )0.1910684002261160.0310971490372594
tau( Zwitserse_Frank , Australische_Dollar )-0.4649322010663811.57915250629336e-07
tau( Canadese_Dollar , Australische_Dollar )0.1052036367376480.235467885319790



Parameters (Session):
Parameters (R input):
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='kendall')
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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations for all pairs of data series',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'tau',1,TRUE)
a<-table.element(a,'p-value',1,TRUE)
a<-table.row.end(a)
n <- length(y[,1])
n
cor.test(y[1,],y[2,],method='kendall')
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste('tau(',dimnames(t(x))[[2]][i])
dum <- paste(dum,',')
dum <- paste(dum,dimnames(t(x))[[2]][j])
dum <- paste(dum,')')
a<-table.element(a,dum,header=TRUE)
r <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,r$estimate)
a<-table.element(a,r$p.value)
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable.tab')