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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 computationSat, 10 Dec 2011 08:33:37 -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/10/t1323524074jcjwpcex2nnbmau.htm/, Retrieved Thu, 31 Oct 2024 23:33:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153529, Retrieved Thu, 31 Oct 2024 23:33:57 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact228
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2010-12-05 17:44:33] [b98453cac15ba1066b407e146608df68]
-   PD  [Kendall tau Correlation Matrix] [WS10 PCM DMA] [2010-12-09 16:41:09] [2099aacba481f75a7f949aa310cab952]
- R  D    [Kendall tau Correlation Matrix] [Workshop 10, Pear...] [2010-12-10 12:51:04] [3635fb7041b1998c5a1332cf9de22bce]
- R  D      [Kendall tau Correlation Matrix] [Paper Pearson Cor...] [2010-12-18 17:31:07] [8081b8996d5947580de3eb171e82db4f]
-   PD        [Kendall tau Correlation Matrix] [Paper Kendall Cor...] [2010-12-18 17:54:50] [8081b8996d5947580de3eb171e82db4f]
-  M              [Kendall tau Correlation Matrix] [workshop 10 kenda...] [2011-12-10 13:33:37] [b00485a169f02477e40dc6f9919569a5] [Current]
- R                 [Kendall tau Correlation Matrix] [] [2012-12-11 12:02:24] [3ba5358ad212dca7c498c7fc6d6ebde5]
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Dataseries X:
631.923	21.454	97.06	130.678
654.294	23.899	97.73	120.877
671.833	24.939	98	137.114
586.840	23.580	97.76	134.406
600.969	24.562	97.48	120.262
625.568	24.696	97.77	130.846
558.110	23.785	97.96	120.343
630.577	23.812	98.22	98.881
628.654	21.917	98.51	115.678
603.184	19.713	98.19	120.796
656.255	19.282	98.37	94.261
600.730	18.788	98.31	89.151
670.326	21.453	98.6	119.880
678.423	24.482	98.96	131.468
641.502	27.474	99.11	155.089
625.311	27.264	99.64	149.581
628.177	27.349	100.02	122.788
589.767	30.632	99.98	143.900
582.471	29.429	100.32	112.115
636.248	30.084	100.44	109.600
599.885	26.290	100.51	117.446
621.694	24.379	101	118.456
637.406	23.335	100.88	101.901
595.994	21.346	100.55	89.940
696.308	21.106	100.82	129.143
674.201	24.514	101.5	126.102
648.861	28.353	102.15	143.048
649.605	30.805	102.39	142.258
672.392	31.348	102.54	131.011
598.396	34.556	102.85	146.471
613.177	33.855	103.47	114.073
638.104	34.787	103.56	114.642
615.632	32.529	103.69	118.226
634.465	29.998	103.49	111.338
638.686	29.257	103.47	108.701
604.243	28.155	103.45	80.512
706.669	30.466	103.48	146.865
677.185	35.704	103.93	137.179
644.328	39.327	103.89	166.536
664.825	39.351	104.4	137.070
605.707	42.234	104.79	127.090
600.136	43.630	104.77	139.966
612.166	43.722	105.13	122.243
599.659	43.121	105.26	109.097
634.210	37.985	104.96	116.591
618.234	37.135	104.75	111.964
613.576	34.646	105.01	109.754
627.200	33.026	105.15	77.609
668.973	35.087	105.2	138.445
651.479	38.846	105.77	127.901
619.661	42.013	105.78	156.615
644.260	43.908	106.26	133.264
579.936	42.868	106.13	143.521
601.752	44.423	106.12	152.139
595.376	44.167	106.57	131.523
588.902	43.636	106.44	113.925
634.341	44.382	106.54	86.495
594.305	42.142	107.1	127.877
606.200	43.452	108.1	107.017
610.926	36.912	108.4	78.716
633.685	42.413	108.84	138.278
639.696	45.344	109.62	144.238
659.451	44.873	110.42	143.679
593.248	47.510	110.67	159.932
606.677	49.554	111.66	136.781
599.434	47.369	112.28	148.173
569.578	45.998	112.87	125.673
629.873	48.140	112.18	105.573
613.438	48.441	112.36	122.405
604.172	44.928	112.16	128.045
658.328	40.454	111.49	94.467
612.633	38.661	111.25	85.573
707.372	37.246	111.36	121.501
739.770	36.843	111.74	125.074
777.535	36.424	111.1	144.979
685.030	37.594	111.33	142.120
730.234	38.144	111.25	124.213
714.154	38.737	111.04	144.407
630.872	34.560	110.97	125.170
719.492	36.080	111.31	109.267
677.023	33.508	111.02	122.354
679.272	35.462	111.07	122.589
718.317	33.374	111.36	104.982
645.672	32.110	111.54	90.542




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153529&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]0 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=153529&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153529&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 time0 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Correlations for all pairs of data series (method=kendall)
werkloosheidvacaturesconsumentprijsindexinschrijvingen
werkloosheid1-0.0910.0890.062
vacatures-0.09110.6210.176
consumentprijsindex0.0890.62110.019
inschrijvingen0.0620.1760.0191

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & werkloosheid & vacatures & consumentprijsindex & inschrijvingen \tabularnewline
werkloosheid & 1 & -0.091 & 0.089 & 0.062 \tabularnewline
vacatures & -0.091 & 1 & 0.621 & 0.176 \tabularnewline
consumentprijsindex & 0.089 & 0.621 & 1 & 0.019 \tabularnewline
inschrijvingen & 0.062 & 0.176 & 0.019 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153529&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]werkloosheid[/C][C]vacatures[/C][C]consumentprijsindex[/C][C]inschrijvingen[/C][/ROW]
[ROW][C]werkloosheid[/C][C]1[/C][C]-0.091[/C][C]0.089[/C][C]0.062[/C][/ROW]
[ROW][C]vacatures[/C][C]-0.091[/C][C]1[/C][C]0.621[/C][C]0.176[/C][/ROW]
[ROW][C]consumentprijsindex[/C][C]0.089[/C][C]0.621[/C][C]1[/C][C]0.019[/C][/ROW]
[ROW][C]inschrijvingen[/C][C]0.062[/C][C]0.176[/C][C]0.019[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153529&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153529&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)
werkloosheidvacaturesconsumentprijsindexinschrijvingen
werkloosheid1-0.0910.0890.062
vacatures-0.09110.6210.176
consumentprijsindex0.0890.62110.019
inschrijvingen0.0620.1760.0191







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
werkloosheid;vacatures-0.0991-0.1419-0.0912
p-value(0.3697)(0.1974)(0.2193)
werkloosheid;consumentprijsindex0.24880.1380.0887
p-value(0.0225)(0.2107)(0.2326)
werkloosheid;inschrijvingen0.11970.0940.062
p-value(0.2781)(0.3944)(0.404)
vacatures;consumentprijsindex0.80030.81680.6207
p-value(0)(0)(0)
vacatures;inschrijvingen0.24170.25910.1756
p-value(0.0267)(0.0175)(0.0181)
consumentprijsindex;inschrijvingen0.02930.03990.0192
p-value(0.791)(0.7189)(0.7958)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
werkloosheid;vacatures & -0.0991 & -0.1419 & -0.0912 \tabularnewline
p-value & (0.3697) & (0.1974) & (0.2193) \tabularnewline
werkloosheid;consumentprijsindex & 0.2488 & 0.138 & 0.0887 \tabularnewline
p-value & (0.0225) & (0.2107) & (0.2326) \tabularnewline
werkloosheid;inschrijvingen & 0.1197 & 0.094 & 0.062 \tabularnewline
p-value & (0.2781) & (0.3944) & (0.404) \tabularnewline
vacatures;consumentprijsindex & 0.8003 & 0.8168 & 0.6207 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
vacatures;inschrijvingen & 0.2417 & 0.2591 & 0.1756 \tabularnewline
p-value & (0.0267) & (0.0175) & (0.0181) \tabularnewline
consumentprijsindex;inschrijvingen & 0.0293 & 0.0399 & 0.0192 \tabularnewline
p-value & (0.791) & (0.7189) & (0.7958) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153529&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]werkloosheid;vacatures[/C][C]-0.0991[/C][C]-0.1419[/C][C]-0.0912[/C][/ROW]
[ROW][C]p-value[/C][C](0.3697)[/C][C](0.1974)[/C][C](0.2193)[/C][/ROW]
[ROW][C]werkloosheid;consumentprijsindex[/C][C]0.2488[/C][C]0.138[/C][C]0.0887[/C][/ROW]
[ROW][C]p-value[/C][C](0.0225)[/C][C](0.2107)[/C][C](0.2326)[/C][/ROW]
[ROW][C]werkloosheid;inschrijvingen[/C][C]0.1197[/C][C]0.094[/C][C]0.062[/C][/ROW]
[ROW][C]p-value[/C][C](0.2781)[/C][C](0.3944)[/C][C](0.404)[/C][/ROW]
[ROW][C]vacatures;consumentprijsindex[/C][C]0.8003[/C][C]0.8168[/C][C]0.6207[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]vacatures;inschrijvingen[/C][C]0.2417[/C][C]0.2591[/C][C]0.1756[/C][/ROW]
[ROW][C]p-value[/C][C](0.0267)[/C][C](0.0175)[/C][C](0.0181)[/C][/ROW]
[ROW][C]consumentprijsindex;inschrijvingen[/C][C]0.0293[/C][C]0.0399[/C][C]0.0192[/C][/ROW]
[ROW][C]p-value[/C][C](0.791)[/C][C](0.7189)[/C][C](0.7958)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153529&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153529&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
werkloosheid;vacatures-0.0991-0.1419-0.0912
p-value(0.3697)(0.1974)(0.2193)
werkloosheid;consumentprijsindex0.24880.1380.0887
p-value(0.0225)(0.2107)(0.2326)
werkloosheid;inschrijvingen0.11970.0940.062
p-value(0.2781)(0.3944)(0.404)
vacatures;consumentprijsindex0.80030.81680.6207
p-value(0)(0)(0)
vacatures;inschrijvingen0.24170.25910.1756
p-value(0.0267)(0.0175)(0.0181)
consumentprijsindex;inschrijvingen0.02930.03990.0192
p-value(0.791)(0.7189)(0.7958)



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')