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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationThu, 22 Dec 2011 14:11:50 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/22/t1324581118aoym4scg5miu8o1.htm/, Retrieved Fri, 03 May 2024 11:04:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159874, Retrieved Fri, 03 May 2024 11:04:38 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Kernel Density Estimation] [PAPER: werklooshe...] [2011-12-22 16:29:04] [f0cb027b41af06223bae4ee77475f3bc]
- RMPD  [Mean Plot] [PAPER: werklooshe...] [2011-12-22 18:01:10] [f0cb027b41af06223bae4ee77475f3bc]
- RMPD    [Kendall tau Correlation Matrix] [PAPER: werklooshe...] [2011-12-22 19:10:34] [f0cb027b41af06223bae4ee77475f3bc]
- R PD        [Kendall tau Correlation Matrix] [PAPER: werklooshe...] [2011-12-22 19:11:50] [6baf48ba14bcb50d9e72b77bece8a45b] [Current]
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Dataseries X:
611	0.072	0.0213
639	0.073	0.0218
630	0.073	0.0290
586	0.073	0.0263
695	0.074	0.0267
552	0.073	0.0181
619	0.074	0.0133
681	0.074	0.0088
421	0.076	0.0128
307	0.076	0.0126
754	0.077	0.0126
690	0.077	0.0129
644	0.078	0.0110
643	0.078	0.0137
608	0.080	0.0121
651	0.081	0.0174
691	0.081	0.0176
627	0.082	0.0148
634	0.081	0.0104
731	0.081	0.0162
475	0.081	0.0149
337	0.080	0.0179
803	0.082	0.0180
722	0.084	0.0158
590	0.084	0.0186
724	0.085	0.0174
627	0.086	0.0159
696	0.085	0.0126
825	0.083	0.0113
677	0.078	0.0192
656	0.078	0.0261
785	0.080	0.0226
412	0.086	0.0241
352	0.089	0.0226
839	0.089	0.0203
729	0.086	0.0286
696	0.083	0.0255
641	0.083	0.0227
695	0.083	0.0226
638	0.084	0.0257
762	0.085	0.0307
635	0.084	0.0276
721	0.086	0.0251
854	0.085	0.0287
418	0.085	0.0314
367	0.085	0.0311
824	0.085	0.0316
687	0.085	0.0247
601	0.085	0.0257
676	0.085	0.0289
740	0.085	0.0263
691	0.086	0.0238
683	0.086	0.0169
594	0.086	0.0196
729	0.086	0.0219
731	0.084	0.0187
386	0.080	0.0160
331	0.079	0.0163
706	0.080	0.0122
715	0.080	0.0121
657	0.080	0.0149
653	0.080	0.0164
642	0.079	0.0166
643	0.079	0.0177
718	0.079	0.0182
654	0.080	0.0178
632	0.079	0.0128
731	0.075	0.0129
392	0.072	0.0137
344	0.070	0.0112
792	0.069	0.0151
852	0.071	0.0224
649	0.071	0.0294
629	0.072	0.0309
685	0.071	0.0346
617	0.069	0.0364
715	0.068	0.0439
715	0.067	0.0415
629	0.067	0.0521
916	0.069	0.0580
531	0.073	0.0591
357	0.074	0.0539
917	0.073	0.0546
828	0.071	0.0472
708	0.070	0.0314
858	0.071	0.0263
775	0.075	0.0232
785	0.077	0.0193
1006	0.078	0.0062
789	0.077	0.0060
734	0.077	-0.0037
906	0.078	-0.0110
532	0.080	-0.0168
387	0.081	-0.0078
991	0.081	-0.0119
841	0.080	-0.0097
892	0.081	-0.0012
782	0.082	0.0026
811	0.083	0.0062
792	0.084	0.0070
978	0.085	0.0166
773	0.085	0.0180
796	0.085	0.0227
946	0.085	0.0246
594	0.085	0.0257
438	0.083	0.0232
1023	0.082	0.0291
868	0.081	0.0301
791	0.079	0.0286
760	0.076	0.0310
779	0.073	0.0322
852	0.071	0.0339
1001	0.070	0.0352
734	0.070	0.0341
996	0.070	0.0335
869	0.070	0.0367
599	0.069	0.0375
426	0.068	0.0360
1138	0.067	0.0355
1091	0.066	0.0357




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159874&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159874&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159874&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' @ jenkins.wessa.net







Correlations for all pairs of data series (method=kendall)
AantalFaillissementenWerkloosheidsgraadInflatie
AantalFaillissementen1-0.0370.061
Werkloosheidsgraad-0.0371-0.173
Inflatie0.061-0.1731

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & AantalFaillissementen & Werkloosheidsgraad & Inflatie \tabularnewline
AantalFaillissementen & 1 & -0.037 & 0.061 \tabularnewline
Werkloosheidsgraad & -0.037 & 1 & -0.173 \tabularnewline
Inflatie & 0.061 & -0.173 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159874&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]AantalFaillissementen[/C][C]Werkloosheidsgraad[/C][C]Inflatie[/C][/ROW]
[ROW][C]AantalFaillissementen[/C][C]1[/C][C]-0.037[/C][C]0.061[/C][/ROW]
[ROW][C]Werkloosheidsgraad[/C][C]-0.037[/C][C]1[/C][C]-0.173[/C][/ROW]
[ROW][C]Inflatie[/C][C]0.061[/C][C]-0.173[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159874&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159874&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=kendall)
AantalFaillissementenWerkloosheidsgraadInflatie
AantalFaillissementen1-0.0370.061
Werkloosheidsgraad-0.0371-0.173
Inflatie0.061-0.1731







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
AantalFaillissementen;Werkloosheidsgraad-0.1098-0.052-0.0372
p-value(0.2325)(0.5726)(0.5573)
AantalFaillissementen;Inflatie0.05940.08780.0605
p-value(0.5195)(0.3405)(0.3282)
Werkloosheidsgraad;Inflatie-0.3809-0.2719-0.1727
p-value(0)(0.0027)(0.0065)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
AantalFaillissementen;Werkloosheidsgraad & -0.1098 & -0.052 & -0.0372 \tabularnewline
p-value & (0.2325) & (0.5726) & (0.5573) \tabularnewline
AantalFaillissementen;Inflatie & 0.0594 & 0.0878 & 0.0605 \tabularnewline
p-value & (0.5195) & (0.3405) & (0.3282) \tabularnewline
Werkloosheidsgraad;Inflatie & -0.3809 & -0.2719 & -0.1727 \tabularnewline
p-value & (0) & (0.0027) & (0.0065) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159874&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]AantalFaillissementen;Werkloosheidsgraad[/C][C]-0.1098[/C][C]-0.052[/C][C]-0.0372[/C][/ROW]
[ROW][C]p-value[/C][C](0.2325)[/C][C](0.5726)[/C][C](0.5573)[/C][/ROW]
[ROW][C]AantalFaillissementen;Inflatie[/C][C]0.0594[/C][C]0.0878[/C][C]0.0605[/C][/ROW]
[ROW][C]p-value[/C][C](0.5195)[/C][C](0.3405)[/C][C](0.3282)[/C][/ROW]
[ROW][C]Werkloosheidsgraad;Inflatie[/C][C]-0.3809[/C][C]-0.2719[/C][C]-0.1727[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.0027)[/C][C](0.0065)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159874&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159874&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
AantalFaillissementen;Werkloosheidsgraad-0.1098-0.052-0.0372
p-value(0.2325)(0.5726)(0.5573)
AantalFaillissementen;Inflatie0.05940.08780.0605
p-value(0.5195)(0.3405)(0.3282)
Werkloosheidsgraad;Inflatie-0.3809-0.2719-0.1727
p-value(0)(0.0027)(0.0065)



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