| | *The author of this computation has been verified* | R Software Module: /rwasp_pairs.wasp (opens new window with default values) | Title produced by software: Kendall tau Correlation Matrix | Date of computation: Tue, 21 Dec 2010 16:21:54 +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/21/t1292949113rqzjup5fp9uh6e8.htm/, Retrieved Tue, 21 Dec 2010 17:31:53 +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/21/t1292949113rqzjup5fp9uh6e8.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 « | 119.880 5124
131.468 4742
155.089 5434
149.581 5684
122.788 6332
143.900 6334
112.115 5636
109.600 5940
117.446 6195
118.456 6022
101.901 4535
89.940 4320
129.143 4872
126.102 4662
143.048 4663
142.258 5491
131.011 6018
146.471 6393
114.073 5610
114.642 5777
118.226 6094
111.338 6478
108.701 5216
80.512 5201
146.865 4784
137.179 4205
166.536 4681
137.070 4896
127.090 5752
139.966 6452
122.243 5995
109.097 5601
116.591 6119
111.964 6569
109.754 5798
77.609 5492
138.445 5018
127.901 4773
156.615 5502
133.264 5908
143.521 5902
152.139 6125
131.523 5419
113.925 5559
86.495 5962
127.877 6023
107.017 5346
78.716 5379
138.278 4859
144.238 5156
143.679 5010
159.932 5508
136.781 6426
148.173 6043
125.673 5499
105.573 5191
122.405 5790
128.045 5949
94.467 5219
85.573 4729 | | 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!
Correlations for all pairs of data series (method=kendall) | | auto-inschrijvingen | verkeersongevallen | auto-inschrijvingen | 1 | 0.026 | verkeersongevallen | 0.026 | 1 |
Correlations for all pairs of data series with p-values | pair | Pearson r | Spearman rho | Kendall tau | auto-inschrijvingen;verkeersongevallen | 0.043 | 0.0242 | 0.026 | p-value | (0.744) | (0.8543) | (0.7692) |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292949113rqzjup5fp9uh6e8/17pru1292948511.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/21/t1292949113rqzjup5fp9uh6e8/17pru1292948511.ps (open in new window) |
| | 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')
| |
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