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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 computationWed, 17 Dec 2008 14:03:12 -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/2008/Dec/17/t1229548089y6j4py71ncbizv5.htm/, Retrieved Sat, 18 May 2024 11:04:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34554, Retrieved Sat, 18 May 2024 11:04:54 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [kendall] [2008-12-17 21:03:12] [c4d631a082add458929a68f815b04b21] [Current]
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Dataseries X:
17409	117.09	87
11514	116.77	96.3
31514	119.39	107.1
27071	122.49	115.2
29462	124.08	106.1
26105	118.29	89.5
22397	112.94	91.3
23843	113.79	97.6
21705	114.43	100.7
18089	118.7		104.6
20764	120.36	94.7
25316	118.27	101.8
17704	118.34	102.5
15548	117.82	105.3
28029	117.65	110.3
29383	118.18	109.8
36438	121.02	117.3
32034	124.78	118.8
22679	131.16	131.3
24319	130.14	125.9
18004	131.75	133.1
17537	134.73	147
20366	135.35	145.8
22782	140.32	164.4
19169	136.35	149.8
13807	131.6		137.7
29743	128.9		151.7
25591	133.89	156.8
29096	138.25	180
26482	146.23	180.4
22405	144.76	170.4
27044	149.3		191.6
17970	156.8		199.5
18730	159.08	218.2
19684	165.12	217.5
19785	163.14	205
18479	153.43	194
10698	151.01	199.3
31956	154.72	219.3
29506	154.58	211.1
34506	155.63	215.2
27165	161.67	240.2
26736	163.51	242.2
23691	162.91	240.7
18157	164.8		255.4
17328	164.98	253
18205	154.54	218.2
20995	148.6		203.7
17382	149.19	205.6
9367		150.61	215.6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001
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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \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=34554&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/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=34554&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34554&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001
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.







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( Wagens , Index )-0.05142857142857140.598203283254512
tau( Wagens , Olie )-0.03429971702850180.725336051485515
tau( Index , Olie )0.8411597271275430

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( Wagens , Index ) & -0.0514285714285714 & 0.598203283254512 \tabularnewline
tau( Wagens , Olie ) & -0.0342997170285018 & 0.725336051485515 \tabularnewline
tau( Index , Olie ) & 0.841159727127543 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34554&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( Wagens , Index )[/C][C]-0.0514285714285714[/C][C]0.598203283254512[/C][/ROW]
[ROW][C]tau( Wagens , Olie )[/C][C]-0.0342997170285018[/C][C]0.725336051485515[/C][/ROW]
[ROW][C]tau( Index , Olie )[/C][C]0.841159727127543[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34554&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34554&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( Wagens , Index )-0.05142857142857140.598203283254512
tau( Wagens , Olie )-0.03429971702850180.725336051485515
tau( Index , Olie )0.8411597271275430



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')