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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 computationTue, 20 Dec 2011 04:07:49 -0500
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/Dec/20/t13243721337gbqzxoxtlp4xqe.htm/, Retrieved Mon, 06 May 2024 06:32:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=157812, Retrieved Mon, 06 May 2024 06:32:35 +0000
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Estimated Impact136
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [pearson corr] [2011-12-20 09:07:49] [0e2c18186cab982e7ba7b89fbe242e59] [Current]
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Dataseries X:
18	1760	89	20465	70
20	1609	56	33629	80
0	192	18	1423	0
26	2182	92	25629	81
31	3367	131	54002	124
36	6727	257	151036	140
23	1619	55	33287	88
30	1507	56	31172	115
30	1682	42	28113	109
26	2812	92	57803	104
24	1943	74	49830	63
30	2017	66	52143	118
21	1702	96	21055	68
25	3034	110	47007	100
18	1379	55	28735	63
19	1517	79	59147	74
33	1637	53	78950	132
15	1169	54	13497	54
34	2384	84	46154	134
18	726	24	53249	57
15	993	55	10726	59
30	2683	96	83700	113
25	1713	70	40400	96
34	2027	50	33797	96
21	1818	81	36205	78
21	1393	28	30165	80
25	2000	154	58534	93
31	1346	85	44663	109
31	2676	115	92556	115
20	2106	43	40078	79
28	1591	43	34711	103
20	1519	43	31076	65
17	2171	101	74608	66
25	3003	121	58092	100
24	2364	52	42009	96
0	1	1	0	0
27	2017	60	36022	105
14	1564	50	23333	51
32	2072	47	53349	108
31	2106	63	92596	124
21	2270	69	49598	81
34	1643	56	44093	136
23	957	29	84205	84
24	2025	77	63369	92
26	1236	46	60132	103
22	1178	91	37403	82
35	744	31	24460	106
21	1976	92	46456	84
31	2224	85	66616	124
26	2561	56	41554	97
22	658	28	22346	82
21	1779	65	30874	79
27	2355	71	68701	97
30	2017	77	35728	107
33	1758	59	29010	126
11	1675	54	23110	40
26	1760	62	38844	96
26	875	23	27084	100
23	1169	65	35139	91
38	2789	93	57476	136
29	1606	56	33277	116
19	2020	76	31141	76
19	1300	58	61281	65
26	1235	35	25820	96
26	1215	32	23284	97
29	1230	38	35378	107
36	2226	67	74990	144
25	2897	65	29653	90
24	1071	38	64622	93
21	340	15	4157	78
19	2704	110	29245	72
12	1247	64	50008	45
30	1422	64	52338	120
21	1535	68	13310	59
34	2593	66	92901	133
32	1397	42	10956	117
28	2162	58	34241	123
28	2513	94	75043	110
21	917	26	21152	75
31	1234	71	42249	114
26	917	66	42005	94
29	1924	59	41152	116
23	853	27	14399	86
25	1398	34	28263	90
22	986	44	17215	87
26	1608	47	48140	99
33	2577	220	62897	132
24	1201	108	22883	96
24	1189	56	41622	91
21	1431	50	40715	77
28	1698	40	65897	104
27	2185	74	76542	97
25	1228	56	37477	94
15	1266	58	53216	60
13	830	36	40911	46
36	2238	111	57021	135
24	1787	68	73116	90
1	223	12	3895	2
24	2254	100	46609	96
31	1952	75	29351	109
4	665	28	2325	15
20	804	22	31747	64
23	1211	49	32665	88
23	1143	57	19249	84
12	710	38	15292	46
16	596	22	5842	59
29	1353	44	33994	116
10	971	32	13018	29
0	0	0	0	0
25	1030	31	98177	91
21	1130	66	37941	76
23	1284	44	31032	83
21	1438	61	32683	84
21	849	57	34545	65
0	78	5	0	0
0	0	0	0	0
23	925	39	27525	84
29	1518	78	66856	99
28	1946	95	28549	112
23	914	37	38610	92
1	778	19	2781	3
29	1713	71	41211	109
17	895	40	22698	71
29	1756	52	41194	106
12	701	40	32689	48
2	285	12	5752	8
21	1774	55	26757	80
25	1071	29	22527	95
29	1582	46	44810	116
2	256	9	0	8
0	98	9	0	0
18	1358	55	100674	56
1	41	3	0	4
21	1771	58	57786	70
0	42	3	0	0
4	528	16	5444	14
0	0	0	0	0
25	1026	45	28470	91
26	1296	38	61849	89
0	81	4	0	0
4	257	13	2179	12
17	914	23	8019	60
21	1178	50	39644	80
22	1080	19	23494	88




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157812&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157812&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157812&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'Herman Ole Andreas Wold' @ wold.wessa.net







Correlations for all pairs of data series (method=pearson)
CPRPGVWSLGNSCMPCHTNSFM
CPR10.6690.5580.6250.982
PGVWS0.66910.8380.6990.683
LGNS0.5580.83810.6180.575
CMPCH0.6250.6990.61810.631
TNSFM0.9820.6830.5750.6311

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & CPR & PGVWS & LGNS & CMPCH & TNSFM \tabularnewline
CPR & 1 & 0.669 & 0.558 & 0.625 & 0.982 \tabularnewline
PGVWS & 0.669 & 1 & 0.838 & 0.699 & 0.683 \tabularnewline
LGNS & 0.558 & 0.838 & 1 & 0.618 & 0.575 \tabularnewline
CMPCH & 0.625 & 0.699 & 0.618 & 1 & 0.631 \tabularnewline
TNSFM & 0.982 & 0.683 & 0.575 & 0.631 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157812&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]CPR[/C][C]PGVWS[/C][C]LGNS[/C][C]CMPCH[/C][C]TNSFM[/C][/ROW]
[ROW][C]CPR[/C][C]1[/C][C]0.669[/C][C]0.558[/C][C]0.625[/C][C]0.982[/C][/ROW]
[ROW][C]PGVWS[/C][C]0.669[/C][C]1[/C][C]0.838[/C][C]0.699[/C][C]0.683[/C][/ROW]
[ROW][C]LGNS[/C][C]0.558[/C][C]0.838[/C][C]1[/C][C]0.618[/C][C]0.575[/C][/ROW]
[ROW][C]CMPCH[/C][C]0.625[/C][C]0.699[/C][C]0.618[/C][C]1[/C][C]0.631[/C][/ROW]
[ROW][C]TNSFM[/C][C]0.982[/C][C]0.683[/C][C]0.575[/C][C]0.631[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=157812&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157812&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=pearson)
CPRPGVWSLGNSCMPCHTNSFM
CPR10.6690.5580.6250.982
PGVWS0.66910.8380.6990.683
LGNS0.5580.83810.6180.575
CMPCH0.6250.6990.61810.631
TNSFM0.9820.6830.5750.6311







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
CPR;PGVWS0.66870.62550.4711
p-value(0)(0)(0)
CPR;LGNS0.55830.5060.3761
p-value(0)(0)(0)
CPR;CMPCH0.62520.57950.4359
p-value(0)(0)(0)
CPR;TNSFM0.98210.97030.8881
p-value(0)(0)(0)
PGVWS;LGNS0.83820.81350.6432
p-value(0)(0)(0)
PGVWS;CMPCH0.69940.64780.4847
p-value(0)(0)(0)
PGVWS;TNSFM0.68270.64390.4805
p-value(0)(0)(0)
LGNS;CMPCH0.61810.61080.4635
p-value(0)(0)(0)
LGNS;TNSFM0.5750.52440.3835
p-value(0)(0)(0)
CMPCH;TNSFM0.63120.59080.4399
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
CPR;PGVWS & 0.6687 & 0.6255 & 0.4711 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CPR;LGNS & 0.5583 & 0.506 & 0.3761 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CPR;CMPCH & 0.6252 & 0.5795 & 0.4359 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CPR;TNSFM & 0.9821 & 0.9703 & 0.8881 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PGVWS;LGNS & 0.8382 & 0.8135 & 0.6432 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PGVWS;CMPCH & 0.6994 & 0.6478 & 0.4847 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PGVWS;TNSFM & 0.6827 & 0.6439 & 0.4805 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
LGNS;CMPCH & 0.6181 & 0.6108 & 0.4635 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
LGNS;TNSFM & 0.575 & 0.5244 & 0.3835 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CMPCH;TNSFM & 0.6312 & 0.5908 & 0.4399 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=157812&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]CPR;PGVWS[/C][C]0.6687[/C][C]0.6255[/C][C]0.4711[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CPR;LGNS[/C][C]0.5583[/C][C]0.506[/C][C]0.3761[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CPR;CMPCH[/C][C]0.6252[/C][C]0.5795[/C][C]0.4359[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CPR;TNSFM[/C][C]0.9821[/C][C]0.9703[/C][C]0.8881[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PGVWS;LGNS[/C][C]0.8382[/C][C]0.8135[/C][C]0.6432[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PGVWS;CMPCH[/C][C]0.6994[/C][C]0.6478[/C][C]0.4847[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PGVWS;TNSFM[/C][C]0.6827[/C][C]0.6439[/C][C]0.4805[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]LGNS;CMPCH[/C][C]0.6181[/C][C]0.6108[/C][C]0.4635[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]LGNS;TNSFM[/C][C]0.575[/C][C]0.5244[/C][C]0.3835[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CMPCH;TNSFM[/C][C]0.6312[/C][C]0.5908[/C][C]0.4399[/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=157812&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=157812&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
CPR;PGVWS0.66870.62550.4711
p-value(0)(0)(0)
CPR;LGNS0.55830.5060.3761
p-value(0)(0)(0)
CPR;CMPCH0.62520.57950.4359
p-value(0)(0)(0)
CPR;TNSFM0.98210.97030.8881
p-value(0)(0)(0)
PGVWS;LGNS0.83820.81350.6432
p-value(0)(0)(0)
PGVWS;CMPCH0.69940.64780.4847
p-value(0)(0)(0)
PGVWS;TNSFM0.68270.64390.4805
p-value(0)(0)(0)
LGNS;CMPCH0.61810.61080.4635
p-value(0)(0)(0)
LGNS;TNSFM0.5750.52440.3835
p-value(0)(0)(0)
CMPCH;TNSFM0.63120.59080.4399
p-value(0)(0)(0)



Parameters (Session):
par1 = pearson ;
Parameters (R input):
par1 = pearson ;
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')