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R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationFri, 24 Dec 2010 22:46:30 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/24/t1293230675ovpq1082ge9k187.htm/, Retrieved Tue, 30 Apr 2024 03:04:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115301, Retrieved Tue, 30 Apr 2024 03:04:47 +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] [] [2010-12-24 22:46:30] [0956ee981dded61b2e7128dae94e5715] [Current]
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Dataseries X:
1221.53	2617.2	10168.52	6957.61	23448.78
1180.55	2506.13	9937.04	6688.49	23007.99
1183.26	2679.07	9202.45	6601.37	23096.32
1141.2	2589.73	9369.35	6229.02	22358.17
1049.33	2457.46	8824.06	5925.22	20536.49
1101.6	2517.3	9537.3	6147.97	21029.81
1030.71	2386.53	9382.64	5965.52	20128.99
1089.41	2453.37	9768.7	5964.33	19765.19
1186.69	2529.66	11057.4	6135.7	21108.59
1169.43	2475.14	11089.94	6153.55	21239.35
1104.49	2525.93	10126.03	5598.46	20608.7
1073.87	2480.93	10198.04	5608.79	20121.99
1115.1	2229.85	10546.44	5957.43	21872.5
1095.63	2169.14	9345.55	5625.95	21821.5
1036.19	2030.98	10034.74	5414.96	21752.87
1057.08	2071.37	10133.23	5675.16	20955.25
1020.62	1953.35	10492.53	5458.04	19724.19
987.48	1748.74	10356.83	5332.14	20573.33
919.32	1696.58	9958.44	4808.64	18378.73
919.14	1900.09	9522.5	4940.82	18171
872.81	1908.64	8828.26	4769.45	15520.99
797.87	1881.46	8109.53	4084.76	13576.02
735.09	2100.18	7568.42	3843.74	12811.57
825.88	2672.2	7994.05	4338.35	13278.21
903.25	3136	8859.56	4810.2	14387.48
896.24	2994.38	8512.27	4669.44	13888.24
968.75	3168.22	8576.98	4987.97	13968.67
1166.36	3751.41	11259.86	5831.02	18016.21
1282.83	3925.43	13072.87	6422.3	21261.89
1267.38	3719.52	13376.81	6479.56	22731.1
1280	3757.12	13481.38	6418.32	22102.01
1400.38	3722.23	14338.54	7096.79	24533.12
1385.59	4127.47	13849.99	6948.82	25755.35
1322.7	4162.5	12525.54	6534.97	22849.2
1330.63	4441.82	13603.02	6748.13	24331.67
1378.55	4325.29	13592.47	6851.75	23455.74
1468.36	4350.83	15307.78	8067.32	27812.65
1481.14	4384.47	15680.67	7870.52	28643.61
1549.38	4639.4	16737.63	8019.22	31352.58
1526.75	4697.86	16785.69	7861.51	27142.47
1473.99	4614.76	16569.09	7638.17	23984.14
1455.27	4471.65	17248.89	7584.14	23184.94
1503.35	4305.23	18138.36	8007.32	21772.73
1530.62	4433.57	17875.75	7883.04	20634.47
1482.37	4388.53	17400.41	7408.87	20318.98
1420.86	4140.3	17287.65	6917.03	19800.93
1406.82	4144.38	17604.12	6715.44	19651.51
1438.24	4070.78	17383.42	6789.11	20106.42
1418.3	3906.01	17225.83	6596.92	19964.72
1400.63	3795.91	16274.33	6309.19	18960.48
1377.94	3703.32	16399.39	6268.92	18324.35
1335.85	3675.8	16127.58	6004.33	17543.05
1303.82	3911.06	16140.76	5859.57	17392.27
1276.66	3912.28	15456.81	5681.97	16971.34
1270.2	3839.25	15505.18	5683.31	16267.62
1270.09	3744.63	15467.33	5692.86	15857.89
1310.61	3549.25	16906.23	6009.89	16661.3
1294.87	3394.14	17059.66	5970.08	15805.04
1280.66	3264.26	16205.43	5796.04	15918.48
1280.08	3328.8	16649.82	5674.15	15753.14
1248.29	3223.98	16111.43	5408.26	14876.43
1249.48	3228.01	14872.15	5193.4	14937.14
1207.01	3112.83	13606.5	4929.07	14386.37
1228.81	3051.67	13574.3	5044.12	15428.52
1220.33	3039.71	12413.6	4829.69	14903.55
1234.18	3125.67	11899.6	4886.5	14880.98
1191.33	3106.54	11584.01	4586.28	14201.06
1191.5		11276.59	4460.63	13867.07
1156.85		11008.9	4184.84	13908.97
1180.59		11668.95	4348.77	13516.88
1203.6		11740.6	4350.49	14195.35
1181.27		11387.59	4254.85	13721.69




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=115301&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=115301&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115301&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Correlations for all pairs of data series (method=spearman)
S&PBel20NikkeiDAXHangSeng
S&P10.8050.7910.6390.281
Bel200.80510.6350.6820.217
Nikkei0.7910.63510.4290.23
DAX0.6390.6820.42910.681
HangSeng0.2810.2170.230.6811

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=spearman) \tabularnewline
  & S&P & Bel20 & Nikkei & DAX & HangSeng \tabularnewline
S&P & 1 & 0.805 & 0.791 & 0.639 & 0.281 \tabularnewline
Bel20 & 0.805 & 1 & 0.635 & 0.682 & 0.217 \tabularnewline
Nikkei & 0.791 & 0.635 & 1 & 0.429 & 0.23 \tabularnewline
DAX & 0.639 & 0.682 & 0.429 & 1 & 0.681 \tabularnewline
HangSeng & 0.281 & 0.217 & 0.23 & 0.681 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115301&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=spearman)[/C][/ROW]
[ROW][C] [/C][C]S&P[/C][C]Bel20[/C][C]Nikkei[/C][C]DAX[/C][C]HangSeng[/C][/ROW]
[ROW][C]S&P[/C][C]1[/C][C]0.805[/C][C]0.791[/C][C]0.639[/C][C]0.281[/C][/ROW]
[ROW][C]Bel20[/C][C]0.805[/C][C]1[/C][C]0.635[/C][C]0.682[/C][C]0.217[/C][/ROW]
[ROW][C]Nikkei[/C][C]0.791[/C][C]0.635[/C][C]1[/C][C]0.429[/C][C]0.23[/C][/ROW]
[ROW][C]DAX[/C][C]0.639[/C][C]0.682[/C][C]0.429[/C][C]1[/C][C]0.681[/C][/ROW]
[ROW][C]HangSeng[/C][C]0.281[/C][C]0.217[/C][C]0.23[/C][C]0.681[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115301&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115301&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=spearman)
S&PBel20NikkeiDAXHangSeng
S&P10.8050.7910.6390.281
Bel200.80510.6350.6820.217
Nikkei0.7910.63510.4290.23
DAX0.6390.6820.42910.681
HangSeng0.2810.2170.230.6811







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
S&P;Bel200.07350.8050.6885
p-value(0.5395)(0)(0)
S&P;Nikkei-0.00430.7910.6415
p-value(0.9714)(0)(0)
S&P;DAX-0.20090.63880.5452
p-value(0.0907)(0)(0)
S&P;HangSeng-0.23190.28080.2634
p-value(0.05)(0.0169)(0.0011)
Bel20;Nikkei-0.05550.63540.463
p-value(0.6435)(0)(0)
Bel20;DAX0.77930.68170.5342
p-value(0)(0)(0)
Bel20;HangSeng-0.33390.21740.2055
p-value(0.0042)(0.0666)(0.0107)
Nikkei;DAX-0.00220.42870.326
p-value(0.9856)(2e-04)(1e-04)
Nikkei;HangSeng0.39460.23040.1945
p-value(6e-04)(0.0515)(0.0157)
DAX;HangSeng0.0890.68130.5773
p-value(0.4571)(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
S&P;Bel20 & 0.0735 & 0.805 & 0.6885 \tabularnewline
p-value & (0.5395) & (0) & (0) \tabularnewline
S&P;Nikkei & -0.0043 & 0.791 & 0.6415 \tabularnewline
p-value & (0.9714) & (0) & (0) \tabularnewline
S&P;DAX & -0.2009 & 0.6388 & 0.5452 \tabularnewline
p-value & (0.0907) & (0) & (0) \tabularnewline
S&P;HangSeng & -0.2319 & 0.2808 & 0.2634 \tabularnewline
p-value & (0.05) & (0.0169) & (0.0011) \tabularnewline
Bel20;Nikkei & -0.0555 & 0.6354 & 0.463 \tabularnewline
p-value & (0.6435) & (0) & (0) \tabularnewline
Bel20;DAX & 0.7793 & 0.6817 & 0.5342 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Bel20;HangSeng & -0.3339 & 0.2174 & 0.2055 \tabularnewline
p-value & (0.0042) & (0.0666) & (0.0107) \tabularnewline
Nikkei;DAX & -0.0022 & 0.4287 & 0.326 \tabularnewline
p-value & (0.9856) & (2e-04) & (1e-04) \tabularnewline
Nikkei;HangSeng & 0.3946 & 0.2304 & 0.1945 \tabularnewline
p-value & (6e-04) & (0.0515) & (0.0157) \tabularnewline
DAX;HangSeng & 0.089 & 0.6813 & 0.5773 \tabularnewline
p-value & (0.4571) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115301&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]S&P;Bel20[/C][C]0.0735[/C][C]0.805[/C][C]0.6885[/C][/ROW]
[ROW][C]p-value[/C][C](0.5395)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]S&P;Nikkei[/C][C]-0.0043[/C][C]0.791[/C][C]0.6415[/C][/ROW]
[ROW][C]p-value[/C][C](0.9714)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]S&P;DAX[/C][C]-0.2009[/C][C]0.6388[/C][C]0.5452[/C][/ROW]
[ROW][C]p-value[/C][C](0.0907)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]S&P;HangSeng[/C][C]-0.2319[/C][C]0.2808[/C][C]0.2634[/C][/ROW]
[ROW][C]p-value[/C][C](0.05)[/C][C](0.0169)[/C][C](0.0011)[/C][/ROW]
[ROW][C]Bel20;Nikkei[/C][C]-0.0555[/C][C]0.6354[/C][C]0.463[/C][/ROW]
[ROW][C]p-value[/C][C](0.6435)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Bel20;DAX[/C][C]0.7793[/C][C]0.6817[/C][C]0.5342[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Bel20;HangSeng[/C][C]-0.3339[/C][C]0.2174[/C][C]0.2055[/C][/ROW]
[ROW][C]p-value[/C][C](0.0042)[/C][C](0.0666)[/C][C](0.0107)[/C][/ROW]
[ROW][C]Nikkei;DAX[/C][C]-0.0022[/C][C]0.4287[/C][C]0.326[/C][/ROW]
[ROW][C]p-value[/C][C](0.9856)[/C][C](2e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Nikkei;HangSeng[/C][C]0.3946[/C][C]0.2304[/C][C]0.1945[/C][/ROW]
[ROW][C]p-value[/C][C](6e-04)[/C][C](0.0515)[/C][C](0.0157)[/C][/ROW]
[ROW][C]DAX;HangSeng[/C][C]0.089[/C][C]0.6813[/C][C]0.5773[/C][/ROW]
[ROW][C]p-value[/C][C](0.4571)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115301&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115301&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
S&P;Bel200.07350.8050.6885
p-value(0.5395)(0)(0)
S&P;Nikkei-0.00430.7910.6415
p-value(0.9714)(0)(0)
S&P;DAX-0.20090.63880.5452
p-value(0.0907)(0)(0)
S&P;HangSeng-0.23190.28080.2634
p-value(0.05)(0.0169)(0.0011)
Bel20;Nikkei-0.05550.63540.463
p-value(0.6435)(0)(0)
Bel20;DAX0.77930.68170.5342
p-value(0)(0)(0)
Bel20;HangSeng-0.33390.21740.2055
p-value(0.0042)(0.0666)(0.0107)
Nikkei;DAX-0.00220.42870.326
p-value(0.9856)(2e-04)(1e-04)
Nikkei;HangSeng0.39460.23040.1945
p-value(6e-04)(0.0515)(0.0157)
DAX;HangSeng0.0890.68130.5773
p-value(0.4571)(0)(0)



Parameters (Session):
par1 = 2 ; par2 = none ; par3 = 2 ; par4 = no ;
Parameters (R input):
par1 = spearman ;
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')