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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, 13 Dec 2011 05:11:57 -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/13/t1323771129vxx3ex4cs6bss5z.htm/, Retrieved Fri, 03 May 2024 02:03:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154336, Retrieved Fri, 03 May 2024 02:03:15 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190
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]
-    D    [Kendall tau Correlation Matrix] [] [2010-12-13 09:50:30] [1251ac2db27b84d4a3ba43449388906b]
- R  D      [Kendall tau Correlation Matrix] [workshop 10: PCM] [2010-12-14 08:19:17] [814f53995537cd15c528d8efbf1cf544]
- RMPD          [Kendall tau Correlation Matrix] [ws10-2] [2011-12-13 10:11:57] [47995d3a8fac585eeb070a274b466f8c] [Current]
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Dataseries X:
194.9	1.79
195.5	1.95
196	  2.26
196.2	2.04
196.2	2.16
196.2	2.75
196.2	2.79
197	  2.88
197.7	3.36
198	  2.97
198.2	3.1
198.5	2.49
198.6	2.2
199.5	2.25
200	  2.09
201.3	2.79
202.2	3.14
202.9	2.93
203.5	2.65
203.5	2.67
204	  2.26
204.1	2.35
204.3	2.13
204.5	2.18
204.8	2.9
205.1	2.63
205.7	2.67
206.5	1.81
206.9	1.33
207.1	0.88
207.8	1.28
208	  1.26
208.5	1.26
208.6	1.29
209	  1.1
209.1	1.37
209.7	1.21
209.8	1.74
209.9	1.76
210	  1.48
210.8	1.04
211.4	1.62
211.7	1.49
212	  1.79
212.2	1.8
212.4	1.58
212.9	1.86
213.4	1.74
213.7	1.59
214	  1.26
214.3	1.13
214.8	1.92
215	  2.61
215.9	2.26
216.4	2.41
216.9	2.26
217.2	2.03
217.5	2.86
217.9	2.55
218.1	2.27
218.6	2.26
218.9	2.57
219.3	3.07
220.4	2.76
220.9	2.51
221	  2.87
221.8	3.14
222	  3.11
222.2	3.16
222.5	2.47
222.9	2.57
223.1	2.89




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154336&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154336&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154336&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'Gertrude Mary Cox' @ cox.wessa.net







Correlations for all pairs of data series (method=kendall)
uurlooninflatie
uurloon10.046
inflatie0.0461

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & uurloon & inflatie \tabularnewline
uurloon & 1 & 0.046 \tabularnewline
inflatie & 0.046 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154336&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]uurloon[/C][C]inflatie[/C][/ROW]
[ROW][C]uurloon[/C][C]1[/C][C]0.046[/C][/ROW]
[ROW][C]inflatie[/C][C]0.046[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154336&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154336&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)
uurlooninflatie
uurloon10.046
inflatie0.0461







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
uurloon;inflatie0.0110.02640.0456
p-value(0.9267)(0.8255)(0.5727)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
uurloon;inflatie & 0.011 & 0.0264 & 0.0456 \tabularnewline
p-value & (0.9267) & (0.8255) & (0.5727) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154336&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]uurloon;inflatie[/C][C]0.011[/C][C]0.0264[/C][C]0.0456[/C][/ROW]
[ROW][C]p-value[/C][C](0.9267)[/C][C](0.8255)[/C][C](0.5727)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154336&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154336&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
uurloon;inflatie0.0110.02640.0456
p-value(0.9267)(0.8255)(0.5727)



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')