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*The author of this computation has been verified*
R Software Module: Patrick.Wessa/rwasp_pairs.wasp (opens new window with default values)
Title produced by software: Kendall tau Correlation Matrix
Date of computation: Fri, 24 Dec 2010 17:39:18 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/24/t1293212284ndletjgz74lvmmn.htm/, Retrieved Fri, 24 Dec 2010 18:38:06 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/24/t1293212284ndletjgz74lvmmn.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
3010 2590 11290 4700 44,51 2910 2080 11620 4960 45,48 3840 2640 10790 4880 53,1 3580 3000 8380 4090 51,88 3140 2350 9370 3450 48,65 3550 2220 10090 3020 54,35 3250 2540 11130 3070 57,52 2820 2700 10530 3720 63,98 2260 2580 10490 3750 62,91 2060 2420 10570 3910 58,54 2120 2090 11170 4120 55,24 2210 2000 11610 4780 56,86 2190 1860 10920 3070 62,99 2180 1980 11570 4100 60,21 2350 2690 12960 3900 62,06 2440 3040 11190 3020 70,26 2370 2450 11920 3220 69,78 2440 2650 14930 4030 68,56 2610 2710 14520 4210 73,67 3040 3230 12970 4510 73,23 3190 3160 13870 4320 61,96 3120 3040 13250 3890 57,81 3170 2630 12760 7280 58,76 3600 2730 14050 9640 62,47 3420 2830 14660 5680 53,68 3650 2320 15010 6320 57,56 4180 2410 15020 5820 62,05 2960 3080 13090 4890 67,49 2710 2260 13190 3320 67,21 2950 2300 11390 2930 71,05 3030 3600 10110 3530 76,93 3770 3380 8240 3690 70,76 4740 3670 7920 3750 77,17 4450 3040 7700 3330 82,34 5550 2840 7920 4790 92,41 5580 2810 8130 5990 90,93 5890 2980 10510 5290 9 etc...
 
Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Correlations for all pairs of data series (method=pearson)
GarnalenKabeljauwTongZeeduivelOlie
Garnalen10.181-0.1910.0320.627
Kabeljauw0.1811-0.038-0.1660.449
Tong-0.191-0.03810.211-0.178
Zeeduivel0.032-0.1660.2111-0.259
Olie0.6270.449-0.178-0.2591


Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Garnalen;Kabeljauw0.18140.3170.2157
p-value(0.1357)(0.0079)(0.009)
Garnalen;Tong-0.1907-0.1662-0.0919
p-value(0.1166)(0.1722)(0.2654)
Garnalen;Zeeduivel0.03240.02070.0056
p-value(0.7914)(0.8661)(0.9463)
Garnalen;Olie0.62650.44850.3227
p-value(0)(1e-04)(1e-04)
Kabeljauw;Tong-0.0382-0.00550.0098
p-value(0.7555)(0.9642)(0.9052)
Kabeljauw;Zeeduivel-0.1658-0.1327-0.0991
p-value(0.1734)(0.2769)(0.2313)
Kabeljauw;Olie0.44940.46870.3299
p-value(1e-04)(0)(1e-04)
Tong;Zeeduivel0.21110.21310.1328
p-value(0.0817)(0.0787)(0.1082)
Tong;Olie-0.1778-0.1271-0.0977
p-value(0.1438)(0.2982)(0.2355)
Zeeduivel;Olie-0.259-0.1818-0.1168
p-value(0.0316)(0.1349)(0.1572)
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/24/t1293212284ndletjgz74lvmmn/1n2qy1293212356.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/24/t1293212284ndletjgz74lvmmn/1n2qy1293212356.ps (open in new window)


 
Parameters (Session):
par1 = 12 ; par2 = -1.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 1 ; par9 = 0 ; par10 = FALSE ;
 
Parameters (R input):
par1 = pearson ; par2 = -1.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 1 ; par9 = 0 ; par10 = FALSE ;
 
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')
 





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Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa


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