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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 computationThu, 12 Nov 2009 07:39:16 -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/12/t12580368529w4hmif3t80f2em.htm/, Retrieved Fri, 03 May 2024 20:31:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=56056, Retrieved Fri, 03 May 2024 20:31:29 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [3/11/2009] [2009-11-02 21:25:00] [b98453cac15ba1066b407e146608df68]
-    D    [Kendall tau Correlation Matrix] [] [2009-11-12 14:39:16] [7dd0431c761b876151627bfbf92230c8] [Current]
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Dataseries X:
1.6	90398	3633	180600	562000
1.8	90269	3597	179835	561000
1.6	90390	3600	179390	555000
1.5	88219	3522	181871	544000
1.5	87032	3503	175153	537000
1.3	87175	3532	177709	543000
1.4	92603	3686	190370	594000
1.4	93571	3748	193423	611000
1.3	94118	3672	193211	613000
1.3	92159	3843	192691	611000
1.2	89528	3905	188728	594000
1.1	89955	3999	192632	595000
1.4	89587	4070	192977	591000
1.2	89488	4084	192941	589000
1.5	88521	4042	192822	584000
1.1	86587	3951	189644	573000
1.3	85159	3933	189056	567000
1.5	84915	3958	190574	569000
1.1	91378	4147	204210	621000
1.4	92729	4221	204888	629000
1.3	92194	4058	201858	628000
1.5	89664	4057	197077	612000
1.6	86285	4089	192734	595000
1.7	86858	4268	196020	597000
1.1	87184	4309	197603	593000
1.6	86629	4303	197965	590000
1.3	85220	4177	195756	580000
1.7	84816	4117	195182	574000
1.6	84831	4065	195728	573000
1.7	84957	3983	196950	573000
1.9	90951	4091	210029	620000
1.8	92134	4067	211516	626000
1.9	91790	4024	205624	620000
1.6	86625	3868	195776	588000
1.5	83324	3800	189706	566000
1.6	82719	3804	190040	557000
1.6	83614	3862	191434	561000
1.7	81640	3792	187925	549000
2	78665	3674	182239	532000
2	77828	3560	182031	526000
1.9	75728	3489	178459	511000
1.7	72187	3412	173278	499000
1.8	79357	3674	191660	555000
1.9	81329	3672	194075	565000
1.7	77304	3463	181591	542000
2	75576	3429	177660	527000
2.1	72932	3400	172607	510000
2.4	74291	3533	176520	514000
2.5	74988	3578	177271	517000
2.5	73302	3544	174540	508000
2.6	70483	3435	170148	493000
2.2	69848	3352	169799	490000
2.5	66466	3213	163249	469000
2.8	67610	3235	167363	478000
2.8	75091	3460	185332	528000
2.9	76207	3385	185969	534000
3	73454	3283	174955	518000
3.1	72008	3295	172088	506000
2.9	71362	3331	172037	502000
2.7	74250	3520	179351	516000




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56056&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56056&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56056&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( inflatie , leeftijd )-0.5734318317771832.85008816018215e-10
tau( inflatie , landbouw )-0.492206991951566.28338595517022e-08
tau( inflatie , diensten )-0.380153285431982.90224876751067e-05
tau( inflatie , totaal )-0.523534088868279.22724067799455e-09
tau( leeftijd , landbouw )0.5098926761554068.76085914924829e-09
tau( leeftijd , diensten )0.5853107344632773.90776300207563e-11
tau( leeftijd , totaal )0.7686232840553130
tau( landbouw , diensten )0.7133975136453698.88178419700125e-16
tau( landbouw , totaal )0.6817808821911281.66533453693773e-14
tau( diensten , totaal )0.7606934933576160

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( inflatie , leeftijd ) & -0.573431831777183 & 2.85008816018215e-10 \tabularnewline
tau( inflatie , landbouw ) & -0.49220699195156 & 6.28338595517022e-08 \tabularnewline
tau( inflatie , diensten ) & -0.38015328543198 & 2.90224876751067e-05 \tabularnewline
tau( inflatie , totaal ) & -0.52353408886827 & 9.22724067799455e-09 \tabularnewline
tau( leeftijd , landbouw ) & 0.509892676155406 & 8.76085914924829e-09 \tabularnewline
tau( leeftijd , diensten ) & 0.585310734463277 & 3.90776300207563e-11 \tabularnewline
tau( leeftijd , totaal ) & 0.768623284055313 & 0 \tabularnewline
tau( landbouw , diensten ) & 0.713397513645369 & 8.88178419700125e-16 \tabularnewline
tau( landbouw , totaal ) & 0.681780882191128 & 1.66533453693773e-14 \tabularnewline
tau( diensten , totaal ) & 0.760693493357616 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56056&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( inflatie , leeftijd )[/C][C]-0.573431831777183[/C][C]2.85008816018215e-10[/C][/ROW]
[ROW][C]tau( inflatie , landbouw )[/C][C]-0.49220699195156[/C][C]6.28338595517022e-08[/C][/ROW]
[ROW][C]tau( inflatie , diensten )[/C][C]-0.38015328543198[/C][C]2.90224876751067e-05[/C][/ROW]
[ROW][C]tau( inflatie , totaal )[/C][C]-0.52353408886827[/C][C]9.22724067799455e-09[/C][/ROW]
[ROW][C]tau( leeftijd , landbouw )[/C][C]0.509892676155406[/C][C]8.76085914924829e-09[/C][/ROW]
[ROW][C]tau( leeftijd , diensten )[/C][C]0.585310734463277[/C][C]3.90776300207563e-11[/C][/ROW]
[ROW][C]tau( leeftijd , totaal )[/C][C]0.768623284055313[/C][C]0[/C][/ROW]
[ROW][C]tau( landbouw , diensten )[/C][C]0.713397513645369[/C][C]8.88178419700125e-16[/C][/ROW]
[ROW][C]tau( landbouw , totaal )[/C][C]0.681780882191128[/C][C]1.66533453693773e-14[/C][/ROW]
[ROW][C]tau( diensten , totaal )[/C][C]0.760693493357616[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56056&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56056&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( inflatie , leeftijd )-0.5734318317771832.85008816018215e-10
tau( inflatie , landbouw )-0.492206991951566.28338595517022e-08
tau( inflatie , diensten )-0.380153285431982.90224876751067e-05
tau( inflatie , totaal )-0.523534088868279.22724067799455e-09
tau( leeftijd , landbouw )0.5098926761554068.76085914924829e-09
tau( leeftijd , diensten )0.5853107344632773.90776300207563e-11
tau( leeftijd , totaal )0.7686232840553130
tau( landbouw , diensten )0.7133975136453698.88178419700125e-16
tau( landbouw , totaal )0.6817808821911281.66533453693773e-14
tau( diensten , totaal )0.7606934933576160



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')