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*Unverified author*

R Software Module

rwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Thu, 06 Nov 2008 08:56:52 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/06/t1225987106bn0ovyyrugfm7uj.htm/, Retrieved Sun, 19 May 2024 06:00:36 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22291, Retrieved Sun, 19 May 2024 06:00:36 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

153

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Mean Plot] [] [2008-11-06 12:58:34] [2c8f052be48bd5ac1a8131ca316a1f62]
F RMPD    [Kendall tau Correlation Matrix] [] [2008-11-06 15:56:52] [0bc7a7cb481099ab86d953798dce52bf] [Current]

Feedback Forum

2008-11-09 15:54:30 [Vincent Vanden Poel] [reply] 
De grafiek alsook de interpretatie zijn volledig correct. Je zou er nog wel op kunnen wijzen dat alle waarden kleiner dan 0,05 betrouwbaar zijn. De RNVM zou dus ook een predictor kunnen zijn maar in mindere mate dan de RCF.
2008-11-11 09:53:55 [] [reply] 
Een goede analyse, ook goed onderbouwd: het verwijzen naar de gegevenstabel maakt de statement (dat de RCF het beste is, met het minste kan dat het door toeval is) enkel sterker. Goed ook om de tabel met gegevens erbij te zetten en nuttige getallen te markeren. Misshien nuttig om toch nog te vermelden dat de beste waarden kleiner zijn dan 0,05, indien men 95% zeker wil zijn dat het vertoonde beeld niet aan het toeval te wijten is. En hierdoor zou de student dan weer de RNVM kunnen vermelden als goede schatter (wel minder goed dan de RCF of cashflow).
2008-11-11 21:04:17 [Peter Van Doninck] [reply] 
De student heeft de grafiek goed getransponeerd. Want de tijd moet in de rijen staan, de variabelen in de kolommen. Het klopt duidelijk dat de p waarde bij de rcf het kleinste is. (sowieso kleiner dan 0,05) De tau correlatie is hier ook het hoogste, waaruit de student correct concludeert dat de cashflow de beste voorspeller is.
2008-11-12 10:39:40 [Steven Vanhooreweghe] [reply] 
Volledig geantwoord. De twee ratio’s lopen inderdaad bijna recht evenredig, dit kan je zien aan de bijna lineaire rechte.

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Dataseries X:

Download CSV

Histogram

Boxplots

4,2	4,8	20,8	0,9	39,6
2,6	-4,2	17,1	0,85	36,1
3	1,6	22,3	0,83	34,4
3,8	5,2	25,1	0,84	33,4
4	9,2	27,7	0,85	34,8
3,5	4,6	24,9	0,83	33,7
4,1	10,6	29,5	0,83	36,3

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132
R Framework error message	The field 'Names of X columns' contains a hard return which cannot be interpreted. Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
R Framework error message & The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'. \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22291&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[ROW][C]R Framework error message[/C][C]The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22291&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22291&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	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132
R Framework error message	The field 'Names of X columns' contains a hard return which cannot be interpreted. Please, resubmit your request without hard returns in the 'Names of X columns'.

Kendall tau rank correlations for all pairs of data series
pair	tau	p-value
tau( RNVM , RNR )	0.714285714285714	0.0301587301587301
tau( RNVM , RCF )	0.523809523809524	0.136111111111111
tau( RNVM , RLEZ )	0.264628062012482	0.427262856745706
tau( RNVM , REV )	0.333333333333333	0.381349206349206
tau( RNR , RCF )	0.80952380952381	0.0107142857142857
tau( RNR , RLEZ )	-0.0529256124024963	0.873844698517373
tau( RNR , REV )	0.0476190476190476	1
tau( RCF , RLEZ )	-0.264628062012482	0.427262856745706
tau( RCF , REV )	-0.142857142857143	0.772619047619048
tau( RLEZ , REV )	0.370479286817474	0.266379923342483

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( RNVM , RNR ) & 0.714285714285714 & 0.0301587301587301 \tabularnewline
tau( RNVM , RCF ) & 0.523809523809524 & 0.136111111111111 \tabularnewline
tau( RNVM , RLEZ ) & 0.264628062012482 & 0.427262856745706 \tabularnewline
tau( RNVM , REV
 ) & 0.333333333333333 & 0.381349206349206 \tabularnewline
tau( RNR , RCF ) & 0.80952380952381 & 0.0107142857142857 \tabularnewline
tau( RNR , RLEZ ) & -0.0529256124024963 & 0.873844698517373 \tabularnewline
tau( RNR , REV
 ) & 0.0476190476190476 & 1 \tabularnewline
tau( RCF , RLEZ ) & -0.264628062012482 & 0.427262856745706 \tabularnewline
tau( RCF , REV
 ) & -0.142857142857143 & 0.772619047619048 \tabularnewline
tau( RLEZ , REV
 ) & 0.370479286817474 & 0.266379923342483 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22291&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( RNVM , RNR )[/C][C]0.714285714285714[/C][C]0.0301587301587301[/C][/ROW]
[ROW][C]tau( RNVM , RCF )[/C][C]0.523809523809524[/C][C]0.136111111111111[/C][/ROW]
[ROW][C]tau( RNVM , RLEZ )[/C][C]0.264628062012482[/C][C]0.427262856745706[/C][/ROW]
[ROW][C]tau( RNVM , REV
 )[/C][C]0.333333333333333[/C][C]0.381349206349206[/C][/ROW]
[ROW][C]tau( RNR , RCF )[/C][C]0.80952380952381[/C][C]0.0107142857142857[/C][/ROW]
[ROW][C]tau( RNR , RLEZ )[/C][C]-0.0529256124024963[/C][C]0.873844698517373[/C][/ROW]
[ROW][C]tau( RNR , REV
 )[/C][C]0.0476190476190476[/C][C]1[/C][/ROW]
[ROW][C]tau( RCF , RLEZ )[/C][C]-0.264628062012482[/C][C]0.427262856745706[/C][/ROW]
[ROW][C]tau( RCF , REV
 )[/C][C]-0.142857142857143[/C][C]0.772619047619048[/C][/ROW]
[ROW][C]tau( RLEZ , REV
 )[/C][C]0.370479286817474[/C][C]0.266379923342483[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22291&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22291&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
pair	tau	p-value
tau( RNVM , RNR )	0.714285714285714	0.0301587301587301
tau( RNVM , RCF )	0.523809523809524	0.136111111111111
tau( RNVM , RLEZ )	0.264628062012482	0.427262856745706
tau( RNVM , REV )	0.333333333333333	0.381349206349206
tau( RNR , RCF )	0.80952380952381	0.0107142857142857
tau( RNR , RLEZ )	-0.0529256124024963	0.873844698517373
tau( RNR , REV )	0.0476190476190476	1
tau( RCF , RLEZ )	-0.264628062012482	0.427262856745706
tau( RCF , REV )	-0.142857142857143	0.772619047619048
tau( RLEZ , REV )	0.370479286817474	0.266379923342483

Figure 1

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code