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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 18:37:28 -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/t1319150510gxq69ysscr4eny1.htm/, Retrieved Thu, 16 May 2024 18:17:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=133385, Retrieved Thu, 16 May 2024 18:17:46 +0000
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Estimated Impact104
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 22:37:28] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
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Dataseries X:
1838	42	11	34	45
1056	50	8	28	37
1115	39	14	29	37
968	40	9	28	34
1384	78	14	46	34
1075	43	8	27	32
1331	46	9	26	32
791	34	11	30	31
1132	57	10	33	31
1112	51	12	33	31
1086	27	8	23	30
865	41	9	28	29
880	58	9	25	28
1162	32	10	32	27
1077	39	8	22	27
1554	42	12	31	27
649	16	8	26	26
760	45	9	24	26
1125	54	15	51	26
895	41	9	31	25
843	56	14	44	25
665	49	12	38	25
782	45	9	29	24
670	16	10	34	24
668	44	8	28	23
628	31	11	35	23
603	41	19	65	23
863	26	9	26	23
620	53	10	29	22
706	31	13	35	22
589	30	9	13	22
670	41	11	28	22
822	42	8	20	22
748	34	12	38	21
714	37	11	30	21
858	25	8	28	21
608	30	13	40	21
584	59	10	32	21
1058	38	8	26	20
564	50	10	28	20
634	33	8	28	20
613	18	10	35	20
694	56	12	20	20
580	80	9	22	20
623	55	10	25	20
846	37	10	31	20
653	47	11	28	19
432	33	10	26	19
773	14	10	33	19
659	34	8	27	18
368	43	10	25	18
474	25	8	14	18
497	31	10	27	18
585	51	9	23	18
936	25	8	28	18
573	33	14	27	18
528	37	12	39	18
817	55	10	30	18
375	19	9	29	18
974	18	8	28	18
400	35	8	28	17
709	42	8	16	17
523	33	11	20	17
611	75	10	28	17
637	20	9	16	17
608	43	8	23	17
557	38	8	24	17
550	43	10	31	17
429	13	9	19	17
566	39	10	30	17
681	39	8	27	17
596	32	6	9	17
578	50	9	29	17
696	14	7	22	16
875	10	10	34	16
874	20	13	35	16
510	45	12	43	16
744	25	11	18	16
405	42	8	23	16
618	19	10	27	15
787	37	9	28	15
432	41	6	17	15
431	19	8	27	15
756	35	8	19	15
592	26	12	40	15
496	11	10	29	15
577	18	11	33	14
417	7	12	33	14
363	17	8	24	14
619	39	6	23	14
573	31	7	24	14
635	16	10	32	14
479	42	4	11	14
676	15	10	13	14
416	27	17	53	14
489	19	8	18	14
520	20	8	24	13
300	12	10	34	13
540	31	10	8	13
433	33	9	9	13
474	12	5	13	13
449	8	8	17	13
1059	18	8	2	13
494	65	8	28	13
494	8	13	29	12
569	14	10	33	12
433	11	8	8	12
371	22	14	19	12
368	10	10	35	12
303	13	12	35	12
384	14	8	26	12
425	33	9	32	12
581	17	10	28	12
459	37	13	25	12
466	18	8	22	12
442	11	7	25	11
498	8	9	19	11
435	23	9	22	11
378	10	9	32	10
526	16	8	21	10
320	13	10	26	10
478	10	11	25	10
376	19	8	10	10
243	16	10	35	10
293	16	9	31	10
619	18	10	30	10
359	34	8	9	9
434	12	10	32	9
316	55	5	20	9
563	7	7	21	9
314	11	6	12	9
447	15	5	17	9
393	14	8	25	8
231	22	10	15	8
474	28	7	24	8
394	24	4	8	8
397	13	10	34	7
297	13	5	17	7
343	11	8	24	7
287	10	10	27	7
209	14	4	3	6
376	8	4	7	6
470	11	9	12	6
413	1	6	13	6
231	0	8	21	6
227	2	8	23	6
171	1	7	11	5
229	3	3	7	5
307	4	0	0	5
147	0	0	0	5
336	12	1	0	5
214	2	4	2	4
206	4	0	0	4
151	7	0	0	2
76	0	3	8	2
29	0	0	0	0
1	0	0	0	0
0	0	0	0	0
5	0	0	0	0
0	0	0	0	0
8	0	0	0	0
0	0	0	0	0
0	0	0	0	0
4	0	0	0	0




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=133385&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=133385&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=133385&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)
PBPRLFMH
P10.4810.340.3610.694
B0.48110.3180.30.594
PR0.340.31810.6390.415
LFM0.3610.30.63910.429
H0.6940.5940.4150.4291

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & P & B & PR & LFM & H \tabularnewline
P & 1 & 0.481 & 0.34 & 0.361 & 0.694 \tabularnewline
B & 0.481 & 1 & 0.318 & 0.3 & 0.594 \tabularnewline
PR & 0.34 & 0.318 & 1 & 0.639 & 0.415 \tabularnewline
LFM & 0.361 & 0.3 & 0.639 & 1 & 0.429 \tabularnewline
H & 0.694 & 0.594 & 0.415 & 0.429 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=133385&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]0.481[/C][C]0.34[/C][C]0.361[/C][C]0.694[/C][/ROW]
[ROW][C]B[/C][C]0.481[/C][C]1[/C][C]0.318[/C][C]0.3[/C][C]0.594[/C][/ROW]
[ROW][C]PR[/C][C]0.34[/C][C]0.318[/C][C]1[/C][C]0.639[/C][C]0.415[/C][/ROW]
[ROW][C]LFM[/C][C]0.361[/C][C]0.3[/C][C]0.639[/C][C]1[/C][C]0.429[/C][/ROW]
[ROW][C]H[/C][C]0.694[/C][C]0.594[/C][C]0.415[/C][C]0.429[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=133385&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=133385&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
P10.4810.340.3610.694
B0.48110.3180.30.594
PR0.340.31810.6390.415
LFM0.3610.30.63910.429
H0.6940.5940.4150.4291







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
P;B0.60160.65760.4809
p-value(0)(0)(0)
P;PR0.53910.45980.3404
p-value(0)(0)(0)
P;LFM0.5220.49750.3609
p-value(0)(0)(0)
P;H0.87760.85830.694
p-value(0)(0)(0)
B;PR0.48940.42690.3181
p-value(0)(0)(0)
B;LFM0.48210.42010.3004
p-value(0)(0)(0)
B;H0.70770.76940.5943
p-value(0)(0)(0)
PR;LFM0.85020.76790.6389
p-value(0)(0)(0)
PR;H0.60820.53590.4146
p-value(0)(0)(0)
LFM;H0.60770.57540.4291
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 & 0.6016 & 0.6576 & 0.4809 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
P;PR & 0.5391 & 0.4598 & 0.3404 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
P;LFM & 0.522 & 0.4975 & 0.3609 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
P;H & 0.8776 & 0.8583 & 0.694 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
B;PR & 0.4894 & 0.4269 & 0.3181 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
B;LFM & 0.4821 & 0.4201 & 0.3004 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
B;H & 0.7077 & 0.7694 & 0.5943 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PR;LFM & 0.8502 & 0.7679 & 0.6389 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PR;H & 0.6082 & 0.5359 & 0.4146 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
LFM;H & 0.6077 & 0.5754 & 0.4291 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=133385&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]0.6016[/C][C]0.6576[/C][C]0.4809[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]P;PR[/C][C]0.5391[/C][C]0.4598[/C][C]0.3404[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]P;LFM[/C][C]0.522[/C][C]0.4975[/C][C]0.3609[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]P;H[/C][C]0.8776[/C][C]0.8583[/C][C]0.694[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]B;PR[/C][C]0.4894[/C][C]0.4269[/C][C]0.3181[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]B;LFM[/C][C]0.4821[/C][C]0.4201[/C][C]0.3004[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]B;H[/C][C]0.7077[/C][C]0.7694[/C][C]0.5943[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PR;LFM[/C][C]0.8502[/C][C]0.7679[/C][C]0.6389[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PR;H[/C][C]0.6082[/C][C]0.5359[/C][C]0.4146[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]LFM;H[/C][C]0.6077[/C][C]0.5754[/C][C]0.4291[/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=133385&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=133385&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;B0.60160.65760.4809
p-value(0)(0)(0)
P;PR0.53910.45980.3404
p-value(0)(0)(0)
P;LFM0.5220.49750.3609
p-value(0)(0)(0)
P;H0.87760.85830.694
p-value(0)(0)(0)
B;PR0.48940.42690.3181
p-value(0)(0)(0)
B;LFM0.48210.42010.3004
p-value(0)(0)(0)
B;H0.70770.76940.5943
p-value(0)(0)(0)
PR;LFM0.85020.76790.6389
p-value(0)(0)(0)
PR;H0.60820.53590.4146
p-value(0)(0)(0)
LFM;H0.60770.57540.4291
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')