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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 computationThu, 20 Oct 2011 18:24:20 -0400
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/Oct/20/t131914959074o6hwulovk960t.htm/, Retrieved Thu, 16 May 2024 16:30:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=133384, Retrieved Thu, 16 May 2024 16:30:51 +0000
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Original text written by user:
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Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [] [2011-10-20 22:24:20] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
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Dataseries X:
895	33	5	25	34
757	56	5	25	23
595	17	5	21	17
725	28	5	21	17
458	16	5	22	15
844	29	5	22	15
408	21	7	35	15
543	19	5	25	14
579	24	5	25	13
482	14	6	29	12
459	17	5	24	11
409	19	5	24	11
366	26	5	24	11
477	14	6	23	11
389	14	5	14	10
388	12	6	19	10
284	12	3	14	10
547	22	5	10	9
311	7	5	25	9
339	12	5	17	9
393	15	7	24	9
403	20	5	25	9
460	15	5	16	9
377	18	5	21	9
314	12	5	20	9
355	34	5	13	9
269	12	5	25	9
488	14	3	9	9
258	25	5	24	9
392	16	5	24	8
384	14	4	13	8
381	15	5	23	8
478	17	6	29	8
334	13	5	15	8
309	19	5	22	8
660	18	5	23	8
249	11	5	25	8
289	8	5	17	8
321	14	6	20	8
344	22	2	9	8
441	23	6	26	8
402	22	6	20	8
388	23	5	23	8
405	11	5	25	8
355	14	5	14	8
328	16	6	25	8
376	13	5	24	8
218	20	5	25	8
429	16	5	25	8
325	14	6	25	8
324	18	4	11	7
379	14	5	25	7
290	22	5	17	7
224	12	5	25	7
314	15	5	23	7
267	13	5	25	7
204	15	0	0	7
248	18	5	7	7
254	11	5	19	7
371	13	5	25	7
469	18	4	16	7
275	15	4	10	7
284	14	5	25	7
277	19	5	21	7
445	26	5	24	7
328	27	5	24	7
319	17	4	19	7
377	14	5	25	7
209	9	4	13	7
325	20	5	20	6
351	11	1	5	6
236	4	5	25	6
239	18	6	16	6
306	19	6	17	6
235	11	5	11	6
357	18	5	12	6
194	8	6	24	6
302	21	5	15	6
224	7	5	24	6
232	4	5	17	6
247	15	5	25	6
160	5	2	10	5
285	12	5	23	5
230	18	5	10	5
219	11	5	20	5
190	7	2	10	5
275	18	5	23	5
292	16	5	19	5
315	9	5	25	5
317	15	6	28	5
196	12	2	3	5
256	11	5	23	5
248	11	5	25	5
222	14	5	13	5
333	11	0	0	5
285	10	5	14	5
330	17	5	11	5
320	14	2	7	5
302	12	5	19	5
259	19	5	10	5
322	17	6	19	5
201	13	5	14	4
169	12	0	0	4
258	14	1	3	4
281	14	6	24	4
252	9	1	4	4
234	10	5	25	4
314	16	8	19	4
319	15	1	1	4
265	12	5	4	4
241	13	4	14	4
110	9	1	4	3
102	3	0	0	3
211	19	0	0	3
177	1	2	4	3
141	10	5	25	3
156	11	5	10	3
141	9	0	0	3
88	8	4	20	3
247	0	2	5	2
128	8	2	3	2
246	1	0	0	2
186	5	5	4	2
84	5	0	0	2
0	3	0	0	0
0	0	0	0	0
21	1	0	0	0
0	0	0	0	0
0	0	0	0	0
0	0	0	0	0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'AstonUniversity' @ aston.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 & 2 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=133384&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=133384&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=133384&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'AstonUniversity' @ aston.wessa.net







Correlations for all pairs of data series (method=kendall)
PBPRLFMH
P10.4990.3670.3580.644
B0.49910.3350.250.457
PR0.3670.33510.610.394
LFM0.3580.250.6110.431
H0.6440.4570.3940.4311

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & P & B & PR & LFM & H \tabularnewline
P & 1 & 0.499 & 0.367 & 0.358 & 0.644 \tabularnewline
B & 0.499 & 1 & 0.335 & 0.25 & 0.457 \tabularnewline
PR & 0.367 & 0.335 & 1 & 0.61 & 0.394 \tabularnewline
LFM & 0.358 & 0.25 & 0.61 & 1 & 0.431 \tabularnewline
H & 0.644 & 0.457 & 0.394 & 0.431 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=133384&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]P[/C][C]B[/C][C]PR[/C][C]LFM[/C][C]H[/C][/ROW]
[ROW][C]P[/C][C]1[/C][C]0.499[/C][C]0.367[/C][C]0.358[/C][C]0.644[/C][/ROW]
[ROW][C]B[/C][C]0.499[/C][C]1[/C][C]0.335[/C][C]0.25[/C][C]0.457[/C][/ROW]
[ROW][C]PR[/C][C]0.367[/C][C]0.335[/C][C]1[/C][C]0.61[/C][C]0.394[/C][/ROW]
[ROW][C]LFM[/C][C]0.358[/C][C]0.25[/C][C]0.61[/C][C]1[/C][C]0.431[/C][/ROW]
[ROW][C]H[/C][C]0.644[/C][C]0.457[/C][C]0.394[/C][C]0.431[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=133384&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=133384&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)
PBPRLFMH
P10.4990.3670.3580.644
B0.49910.3350.250.457
PR0.3670.33510.610.394
LFM0.3580.250.6110.431
H0.6440.4570.3940.4311







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
P;B0.72140.66370.4988
p-value(0)(0)(0)
P;PR0.49580.47130.367
p-value(0)(0)(0)
P;LFM0.52360.48650.3578
p-value(0)(0)(0)
P;H0.85050.79960.6441
p-value(0)(0)(0)
B;PR0.45610.42630.3348
p-value(0)(0)(0)
B;LFM0.4350.34830.2503
p-value(0)(0)(1e-04)
B;H0.69230.59150.4569
p-value(0)(0)(0)
PR;LFM0.83530.71030.6102
p-value(0)(0)(0)
PR;H0.45030.48440.3936
p-value(0)(0)(0)
LFM;H0.53370.56180.4313
p-value(0)(0)(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
P;B & 0.7214 & 0.6637 & 0.4988 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
P;PR & 0.4958 & 0.4713 & 0.367 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
P;LFM & 0.5236 & 0.4865 & 0.3578 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
P;H & 0.8505 & 0.7996 & 0.6441 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
B;PR & 0.4561 & 0.4263 & 0.3348 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
B;LFM & 0.435 & 0.3483 & 0.2503 \tabularnewline
p-value & (0) & (0) & (1e-04) \tabularnewline
B;H & 0.6923 & 0.5915 & 0.4569 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PR;LFM & 0.8353 & 0.7103 & 0.6102 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PR;H & 0.4503 & 0.4844 & 0.3936 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
LFM;H & 0.5337 & 0.5618 & 0.4313 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=133384&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]P;B[/C][C]0.7214[/C][C]0.6637[/C][C]0.4988[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]P;PR[/C][C]0.4958[/C][C]0.4713[/C][C]0.367[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]P;LFM[/C][C]0.5236[/C][C]0.4865[/C][C]0.3578[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]P;H[/C][C]0.8505[/C][C]0.7996[/C][C]0.6441[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]B;PR[/C][C]0.4561[/C][C]0.4263[/C][C]0.3348[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]B;LFM[/C][C]0.435[/C][C]0.3483[/C][C]0.2503[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]B;H[/C][C]0.6923[/C][C]0.5915[/C][C]0.4569[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PR;LFM[/C][C]0.8353[/C][C]0.7103[/C][C]0.6102[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PR;H[/C][C]0.4503[/C][C]0.4844[/C][C]0.3936[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]LFM;H[/C][C]0.5337[/C][C]0.5618[/C][C]0.4313[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=133384&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=133384&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
P;B0.72140.66370.4988
p-value(0)(0)(0)
P;PR0.49580.47130.367
p-value(0)(0)(0)
P;LFM0.52360.48650.3578
p-value(0)(0)(0)
P;H0.85050.79960.6441
p-value(0)(0)(0)
B;PR0.45610.42630.3348
p-value(0)(0)(0)
B;LFM0.4350.34830.2503
p-value(0)(0)(1e-04)
B;H0.69230.59150.4569
p-value(0)(0)(0)
PR;LFM0.83530.71030.6102
p-value(0)(0)(0)
PR;H0.45030.48440.3936
p-value(0)(0)(0)
LFM;H0.53370.56180.4313
p-value(0)(0)(0)



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')