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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, 21 Dec 2010 14:35:52 +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/21/t1292942087azubd0bzds4ff3h.htm/, Retrieved Sun, 19 May 2024 17:11:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113620, Retrieved Sun, 19 May 2024 17:11:31 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
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Estimated Impact125
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [Pearson correlati...] [2010-12-21 14:35:52] [5f761c4a622da19727fd2adf71158b48] [Current]
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Dataseries X:
216234	627	1,59
213586	696	1,26
209465	825	1,13
204045	677	1,92
200237	656	2,61
203666	785	2,26
241476	412	2,41
260307	352	2,26
243324	839	2,03
244460	729	2,86
233575	696	2,55
237217	641	2,27
235243	695	2,26
230354	638	2,57
227184	762	3,07
221678	635	2,76
217142	721	2,51
219452	854	2,87
256446	418	3,14
265845	367	3,11
248624	824	3,16
241114	687	2,47
229245	601	2,57
231805	676	2,89
219277	740	2,63
219313	691	2,38
212610	683	1,69
214771	594	1,96
211142	729	2,19
211457	731	1,87
240048	386	1,6
240636	331	1,63
230580	707	1,22
208795	715	1,21
197922	657	1,49
194596	653	1,64
194581	642	1,66
185686	643	1,77
178106	718	1,82
172608	654	1,78
167302	632	1,28
168053	731	1,29
202300	392	1,37
202388	344	1,12
182516	792	1,51
173476	852	2,24
166444	649	2,94
171297	629	3,09
169701	685	3,46
164182	617	3,64
161914	715	4,39
159612	715	4,15
151001	629	5,21
158114	916	5,8
186530	531	5,91
187069	357	5,39
174330	917	5,46
169362	828	4,72
166827	708	3,14
178037	858	2,63
186413	775	2,32
189226	785	1,93
191563	1006	0,62
188906	789	0,6
186005	734	-0,37
195309	906	-1,1
223532	532	-1,68
226899	387	-0,78
214126	991	-1,19
206903	841	-0,97
204442	892	-0,12
220375	782	0,26




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113620&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113620&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113620&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'Gwilym Jenkins' @ 72.249.127.135







Correlations for all pairs of data series (method=pearson)
WerklozenFaillissementenInflatie
Werklozen1-0.335-0.254
Faillissementen-0.3351-0.091
Inflatie-0.254-0.0911

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Werklozen & Faillissementen & Inflatie \tabularnewline
Werklozen & 1 & -0.335 & -0.254 \tabularnewline
Faillissementen & -0.335 & 1 & -0.091 \tabularnewline
Inflatie & -0.254 & -0.091 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113620&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Werklozen[/C][C]Faillissementen[/C][C]Inflatie[/C][/ROW]
[ROW][C]Werklozen[/C][C]1[/C][C]-0.335[/C][C]-0.254[/C][/ROW]
[ROW][C]Faillissementen[/C][C]-0.335[/C][C]1[/C][C]-0.091[/C][/ROW]
[ROW][C]Inflatie[/C][C]-0.254[/C][C]-0.091[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113620&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113620&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=pearson)
WerklozenFaillissementenInflatie
Werklozen1-0.335-0.254
Faillissementen-0.3351-0.091
Inflatie-0.254-0.0911







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Werklozen;Faillissementen-0.3351-0.2352-0.1583
p-value(0.004)(0.0467)(0.0495)
Werklozen;Inflatie-0.2543-0.1434-0.0783
p-value(0.0311)(0.2294)(0.3309)
Faillissementen;Inflatie-0.0911-0.103-0.0753
p-value(0.4466)(0.3891)(0.3505)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Werklozen;Faillissementen & -0.3351 & -0.2352 & -0.1583 \tabularnewline
p-value & (0.004) & (0.0467) & (0.0495) \tabularnewline
Werklozen;Inflatie & -0.2543 & -0.1434 & -0.0783 \tabularnewline
p-value & (0.0311) & (0.2294) & (0.3309) \tabularnewline
Faillissementen;Inflatie & -0.0911 & -0.103 & -0.0753 \tabularnewline
p-value & (0.4466) & (0.3891) & (0.3505) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113620&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]Werklozen;Faillissementen[/C][C]-0.3351[/C][C]-0.2352[/C][C]-0.1583[/C][/ROW]
[ROW][C]p-value[/C][C](0.004)[/C][C](0.0467)[/C][C](0.0495)[/C][/ROW]
[ROW][C]Werklozen;Inflatie[/C][C]-0.2543[/C][C]-0.1434[/C][C]-0.0783[/C][/ROW]
[ROW][C]p-value[/C][C](0.0311)[/C][C](0.2294)[/C][C](0.3309)[/C][/ROW]
[ROW][C]Faillissementen;Inflatie[/C][C]-0.0911[/C][C]-0.103[/C][C]-0.0753[/C][/ROW]
[ROW][C]p-value[/C][C](0.4466)[/C][C](0.3891)[/C][C](0.3505)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113620&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113620&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
Werklozen;Faillissementen-0.3351-0.2352-0.1583
p-value(0.004)(0.0467)(0.0495)
Werklozen;Inflatie-0.2543-0.1434-0.0783
p-value(0.0311)(0.2294)(0.3309)
Faillissementen;Inflatie-0.0911-0.103-0.0753
p-value(0.4466)(0.3891)(0.3505)



Parameters (Session):
par1 = pearson ;
Parameters (R input):
par1 = pearson ;
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')