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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationSat, 22 Dec 2007 06:19:55 -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/2007/Dec/22/t1198328499cjio19saalm3ydx.htm/, Retrieved Sun, 05 May 2024 01:10:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4820, Retrieved Sun, 05 May 2024 01:10:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsgedifferentieerd
Estimated Impact282

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [Kendall Tau (diff)] [2007-12-22 13:19:55] [0eafefa7b02d47065fceb6c46f54fbf9] [Current]
- R  D    [Kendall tau Correlation Matrix] [Taak] [2008-12-17 21:39:36] [a0c3f7f6bb6d3d65b8bcf25e6a3c7584]
- RMPD    [Cross Correlation Function] [] [2008-12-17 21:45:12] [f3161d5a04a14312cd010aa8f92941cc]
-   P       [Cross Correlation Function] [] [2008-12-17 21:48:00] [f3161d5a04a14312cd010aa8f92941cc]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0	1	-1,3	16
0	1,1	0,4	38
0	1,2	-6,3	41
0	0,5	0,4	43
0	-1	-1,3	42
0	-0,8	0,7	40
0	-1,1	-3,5	48
0	-0,4	2	46
0	1,2	3,9	51
0	0,6	7,8	52
0	-0,1	7	55
0	0,3	-0,9	55
0	0,2	3	46
0	-0,2	-0,7	38
0,2	-0,8	8,8	43
4,1	-0,8	-8,1	43
-1	1	2,7	44
0	-0,1	2,5	45
4	-0,8	11,8	35
1,9	0,9	-1,5	36
1,1	1,8	-7,7	36
0	0,1	-13,5	25
0	-0,1	-1,6	31
0,7	-0,8	-1,8	35
1,6	-2,1	2,3	46
2	-0,3	3,1	47
0	1,4	-2,5	40
4,8	-10,8	7,1	29
-1,5	9,4	-7,5	28
-4,4	0,5	-4,8	29
-2,7	1,7	-7,1	29
2,8	1,1	2,7	30
0,7	0	10,5	26
0,4	-2,1	7,6	27
-1,9	-1,7	2,8	18
-0,7	0,4	-5,6	15
0	1,6	-5	1
0	0,5	-2,9	1
0	-0,6	-5,2	2
8,3	0,1	9,7	2
1,4	0	6,9	1
0	-0,6	9,3	-4
-1,2	-1,42E-14	-1,4	1
0	-0,4	1,1	6
5,1	-0,1	-11,2	4
-3,7	1,4	-0,5	-1
-4,1	0,7	-8,9	-3
3,5	-0,9	2,4	-8
0	-1	1,9	-24
1,2	-0,1	0,5	-29
0	0,4	-0,1	-40
0	-0,3	-2,8	-32
0,2	0,2	-1,8	-41
-1,1	0,9	-0,9	-48
-3,9	-0,5	-0,9	-48
0,2	-0,5	1,2	-62
-0,4	0,6	6,6	-74
-0,2	0,8	5,1	-65
-0,7	-0,2	5,6	-61
2,2	-1,42E-14	1,3	-78
2,2	0,2	2,1	-61

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4820&T=0

[TABLE]
[ROW][C]Summary of compuational 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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4820&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4820&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( energieprijzen , industriële_productie )-0.2492855301070330.00805600418938776
tau( energieprijzen , nieuwe_personenwagens )0.2044666820144430.0282971388824316
tau( energieprijzen , werkloosheid )0.06258313750339450.503775491712184
tau( industriële_productie , nieuwe_personenwagens )-0.2138610496701020.0161688477841671
tau( industriële_productie , werkloosheid )-0.02337264904238150.793481371372563
tau( nieuwe_personenwagens , werkloosheid )0.03360914190675040.704051484710579

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( energieprijzen , industriële_productie ) & -0.249285530107033 & 0.00805600418938776 \tabularnewline
tau( energieprijzen , nieuwe_personenwagens ) & 0.204466682014443 & 0.0282971388824316 \tabularnewline
tau( energieprijzen , werkloosheid ) & 0.0625831375033945 & 0.503775491712184 \tabularnewline
tau( industriële_productie , nieuwe_personenwagens ) & -0.213861049670102 & 0.0161688477841671 \tabularnewline
tau( industriële_productie , werkloosheid ) & -0.0233726490423815 & 0.793481371372563 \tabularnewline
tau( nieuwe_personenwagens , werkloosheid ) & 0.0336091419067504 & 0.704051484710579 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4820&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( energieprijzen , industriële_productie )[/C][C]-0.249285530107033[/C][C]0.00805600418938776[/C][/ROW]
[ROW][C]tau( energieprijzen , nieuwe_personenwagens )[/C][C]0.204466682014443[/C][C]0.0282971388824316[/C][/ROW]
[ROW][C]tau( energieprijzen , werkloosheid )[/C][C]0.0625831375033945[/C][C]0.503775491712184[/C][/ROW]
[ROW][C]tau( industriële_productie , nieuwe_personenwagens )[/C][C]-0.213861049670102[/C][C]0.0161688477841671[/C][/ROW]
[ROW][C]tau( industriële_productie , werkloosheid )[/C][C]-0.0233726490423815[/C][C]0.793481371372563[/C][/ROW]
[ROW][C]tau( nieuwe_personenwagens , werkloosheid )[/C][C]0.0336091419067504[/C][C]0.704051484710579[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4820&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4820&T=1

As an alternative you can also use a QR Code:  
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( energieprijzen , industriële_productie )-0.2492855301070330.00805600418938776
tau( energieprijzen , nieuwe_personenwagens )0.2044666820144430.0282971388824316
tau( energieprijzen , werkloosheid )0.06258313750339450.503775491712184
tau( industriële_productie , nieuwe_personenwagens )-0.2138610496701020.0161688477841671
tau( industriële_productie , werkloosheid )-0.02337264904238150.793481371372563
tau( nieuwe_personenwagens , werkloosheid )0.03360914190675040.704051484710579


Figures (Output of Computation)

Input Parameters & R Code

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')