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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, 14 Nov 2009 13:47:48 -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/14/t1258231740vz6zbuixszvrhqb.htm/, Retrieved Sun, 28 Apr 2024 15:59:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=57258, Retrieved Sun, 28 Apr 2024 15:59:33 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact167
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Notched Boxplots] [shw-ws6] [2009-11-13 12:26:10] [2663058f2a5dda519058ac6b2228468f]
- RMPD    [Kendall tau Correlation Matrix] [Workshop6/Kendall...] [2009-11-14 20:47:48] [f94f05f163a3ee3ab544c4fef41db0eb] [Current]
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Dataseries X:
114.08	136.49	129.57	129.41
112.95	142.62	130.02	136.76
135.31	141.71	132.91	136.76
134.31	149.51	138.25	127.94
133.03	147.39	142.68	120.59
140.11	131.96	139.61	122.06
124.69	136.38	138.49	125.00
131.68	127.34	140.48	126.47
150.95	133.85	137.68	125.00
137.26	125.14	135.09	120.59
130.51	141.25	129.46	119.12
143.15	149.32	128.09	116.18
118.01	120.92	128.09	126.47
122.56	134.85	130.81	127.94
147.97	131.93	130.42	127.94
135.74	134.22	127.86	125.00
151.62	143.07	125.42	123.53
154.82	145.37	126.17	125.00
145.59	134.32	128.80	127.94
147.12	126.31	127.04	127.94
175.86	162.21	127.91	126.47
140.66	124.09	130.58	125.00
152.69	153.91	135.89	122.06
154.38	154.34	134.62	117.65
132.45	138.70	134.98	120.59
136.44	150.98	136.33	119.12
153.24	146.39	135.44	119.12
154.11	178.30	134.20	117.65
155.93	168.23	137.08	116.18
142.53	162.52	140.61	116.18
148.73	158.86	138.33	117.65
147.73	152.17	139.13	117.65
166.79	171.01	140.92	116.18
144.30	171.49	143.83	117.65
156.07	189.62	143.78	113.24
161.70	177.46	142.80	105.88
152.10	179.98	145.96	110.29
140.45	156.96	144.96	107.35
155.56	167.89	147.88	102.94
174.53	194.78	151.40	102.94
167.16	192.78	156.26	102.94
159.48	165.06	155.05	105.88
173.22	196.60	156.62	107.35
176.13	151.64	156.94	104.41
180.31	187.02	165.23	100.00
185.84	210.99	167.62	94.12
169.43	219.08	165.55	89.71
195.25	235.68	165.51	95.59
174.99	241.44	167.82	113.24
156.42	187.46	159.36	116.18
182.08	229.57	152.92	110.29
182.00	208.44	141.77	101.47
153.28	215.09	135.49	97.06
136.72	217.00	143.12	101.47
130.19	171.08	140.89	113.24
132.04	178.41	136.05	117.65
143.89	196.34	138.87	117.65
133.38	172.11	140.36	113.24
127.98	154.93	145.26	107.35
150.45	182.26	149.15	108.82
133.55	181.74	149.92	119.12




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=57258&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=57258&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57258&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' @ 72.249.127.135







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( InvoerEU , InvoerAM )0.4415300546448094.95324563365429e-07
tau( InvoerEU , USD )0.3372506275171040.000123228539346654
tau( InvoerEU , Werkloosh )-0.4526269925439614.33950484092606e-07
tau( InvoerAM , USD )0.5285597355089781.76939929374953e-09
tau( InvoerAM , Werkloosh )-0.6202666194120954.35767140297698e-12
tau( USD , Werkloosh )-0.5852222164000176.48343975566971e-11

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( InvoerEU , InvoerAM ) & 0.441530054644809 & 4.95324563365429e-07 \tabularnewline
tau( InvoerEU , USD ) & 0.337250627517104 & 0.000123228539346654 \tabularnewline
tau( InvoerEU , Werkloosh ) & -0.452626992543961 & 4.33950484092606e-07 \tabularnewline
tau( InvoerAM , USD ) & 0.528559735508978 & 1.76939929374953e-09 \tabularnewline
tau( InvoerAM , Werkloosh ) & -0.620266619412095 & 4.35767140297698e-12 \tabularnewline
tau( USD , Werkloosh ) & -0.585222216400017 & 6.48343975566971e-11 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=57258&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( InvoerEU , InvoerAM )[/C][C]0.441530054644809[/C][C]4.95324563365429e-07[/C][/ROW]
[ROW][C]tau( InvoerEU , USD )[/C][C]0.337250627517104[/C][C]0.000123228539346654[/C][/ROW]
[ROW][C]tau( InvoerEU , Werkloosh )[/C][C]-0.452626992543961[/C][C]4.33950484092606e-07[/C][/ROW]
[ROW][C]tau( InvoerAM , USD )[/C][C]0.528559735508978[/C][C]1.76939929374953e-09[/C][/ROW]
[ROW][C]tau( InvoerAM , Werkloosh )[/C][C]-0.620266619412095[/C][C]4.35767140297698e-12[/C][/ROW]
[ROW][C]tau( USD , Werkloosh )[/C][C]-0.585222216400017[/C][C]6.48343975566971e-11[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=57258&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57258&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( InvoerEU , InvoerAM )0.4415300546448094.95324563365429e-07
tau( InvoerEU , USD )0.3372506275171040.000123228539346654
tau( InvoerEU , Werkloosh )-0.4526269925439614.33950484092606e-07
tau( InvoerAM , USD )0.5285597355089781.76939929374953e-09
tau( InvoerAM , Werkloosh )-0.6202666194120954.35767140297698e-12
tau( USD , Werkloosh )-0.5852222164000176.48343975566971e-11



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')