Free Statistics

of Irreproducible Research!

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 computationFri, 06 Nov 2009 00:23:24 -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/2009/Nov/06/t1257492265rb2fcivsxcs6t9e.htm/, Retrieved Sun, 28 Apr 2024 15:09:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54215, Retrieved Sun, 28 Apr 2024 15:09:06 +0000
QR Codes:

Original text written by user:Kendall tau correlation matrix van het leningsbedrag, schulden op consumentenkredieten, rentevoet autolening en inflatie in België
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [shw6: Kendall tau...] [2009-11-06 07:23:24] [7a39e26d7a09dd77604df90cb29f8d39] [Current]
Feedback Forum

Post a new message
Dataseries X:
24710.92	2180995.35	4.79	2.86
23983.59	2191117.36	5.95	2.55
24434.12	2219483.98	5.46	2.27
23939.23	2217992.79	5.75	2.26
24290.02	2209675.04	5.15	2.57
24117.63	2204327.56	4.96	3.07
23724.64	2217758.16	5.28	2.76
22989.44	2218743.78	5.73	2.51
23716.86	2231760.73	5.75	2.87
25058.83	2242745.96	5.88	3.14
25059	2269344.45	6.3	3.11
23579.18	2277708.79	6.74	3.16
24209.03	2281332.03	6.75	2.47
24173.67	2293500.47	7.34	2.57
24706.39	2319792.57	6.64	2.89
24522.12	2320736.3	6.62	2.63
24766.15	2303874.92	6.32	2.38
25940.04	2291488.94	5.32	1.69
24985.78	2299751.72	5.68	1.96
24788	2313222.41	6.18	2.19
26544.56	2314078.67	5.02	1.87
28019.08	2325555.72	2.1	1.6
27285.71	2353668.83	4	1.63
29161.16	2363959.25	3	1.22
28357.73	2366135.5	4.73	1.21
27979.91	2388164.24	5.14	1.49
27543.95	2415043.36	5.81	1.64
27397.53	2411619.15	6.24	1.66
27623.59	2400100.64	4.49	1.77
27736.07	2398536.15	4.22	1.82
27803.79	2404054.33	4.88	1.78
27779.55	2421077.9	5.18	1.28
27524.13	2430396.04	5.19	1.29
27582.72	2445739.91	5.06	1.37
28638.95	2484702.11	4.65	1.12
28825.78	2499887.85	4.83	1.51
30132.61	2506371.6	4.6	2.24
29326.85	2526847.52	4.72	2.94
29075.62	2551947.88	4.33	3.09
28230.63	2549403.15	4.97	3.46
28118.36	2533567.74	5.37	3.64
28173.29	2529577.21	4.19	4.39
27396.91	2541049.08	4.54	4.15
24578.55	2547421.64	5.82	5.21
24504.77	2555613.49	5.49	5.8
27582.37	2566290.53	3.28	5.91
26920.31	2580919.67	5.11	5.39
25426.68	2587978.57	6.24	5.46
25390.8	2580098.72	6.41	4.72
25041.16	2579086.96	6.43	3.14
22769.42	2592127.5	8.42	2.63
22921.89	2586944.73	8.23	2.32
26267.63	2548600.43	3.17	1.93
27364.67	2516994.05	2.72	0.62
28382.59	2500125.23	3	0.6
29132.81	2493360.56	3.47	-0.37
28214.51	2475571.42	3.88	-1.1
28865.73	2460157.93	3.43	-1.68
24405.35	2467502.24	4.06	-0.78




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=54215&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=54215&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54215&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







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( Leningsbedrag , Schulden )0.2951490356516660.000958472363950413
tau( Leningsbedrag , Rentevoet )-0.4855222693863895.69499199074139e-08
tau( Leningsbedrag , Inflatie )-0.2819538961978790.00162025791201314
tau( Schulden , Rentevoet )-0.1181632511036760.186480972178004
tau( Schulden , Inflatie )0.02924832948110780.743671412295792
tau( Rentevoet , Inflatie )0.3038641686182670.000687718718476393

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( Leningsbedrag , Schulden ) & 0.295149035651666 & 0.000958472363950413 \tabularnewline
tau( Leningsbedrag , Rentevoet ) & -0.485522269386389 & 5.69499199074139e-08 \tabularnewline
tau( Leningsbedrag , Inflatie ) & -0.281953896197879 & 0.00162025791201314 \tabularnewline
tau( Schulden , Rentevoet ) & -0.118163251103676 & 0.186480972178004 \tabularnewline
tau( Schulden , Inflatie ) & 0.0292483294811078 & 0.743671412295792 \tabularnewline
tau( Rentevoet , Inflatie ) & 0.303864168618267 & 0.000687718718476393 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54215&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( Leningsbedrag , Schulden )[/C][C]0.295149035651666[/C][C]0.000958472363950413[/C][/ROW]
[ROW][C]tau( Leningsbedrag , Rentevoet )[/C][C]-0.485522269386389[/C][C]5.69499199074139e-08[/C][/ROW]
[ROW][C]tau( Leningsbedrag , Inflatie )[/C][C]-0.281953896197879[/C][C]0.00162025791201314[/C][/ROW]
[ROW][C]tau( Schulden , Rentevoet )[/C][C]-0.118163251103676[/C][C]0.186480972178004[/C][/ROW]
[ROW][C]tau( Schulden , Inflatie )[/C][C]0.0292483294811078[/C][C]0.743671412295792[/C][/ROW]
[ROW][C]tau( Rentevoet , Inflatie )[/C][C]0.303864168618267[/C][C]0.000687718718476393[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54215&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54215&T=1

As an alternative you can also use a 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( Leningsbedrag , Schulden )0.2951490356516660.000958472363950413
tau( Leningsbedrag , Rentevoet )-0.4855222693863895.69499199074139e-08
tau( Leningsbedrag , Inflatie )-0.2819538961978790.00162025791201314
tau( Schulden , Rentevoet )-0.1181632511036760.186480972178004
tau( Schulden , Inflatie )0.02924832948110780.743671412295792
tau( Rentevoet , Inflatie )0.3038641686182670.000687718718476393



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')