| workshop 10 pearson | *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: Mon, 13 Dec 2010 10:17:11 +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/13/t1292236311hkp06j663fmhg58.htm/, Retrieved Mon, 13 Dec 2010 11:31:51 +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/13/t1292236311hkp06j663fmhg58.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 « | 627 216.234
696 213.586
825 209.465
677 204.045
656 200.237
785 203.666
412 241.476
352 260.307
839 243.324
729 244.460
696 233.575
641 237.217
695 235.243
638 230.354
762 227.184
635 221.678
721 217.142
854 219.452
418 256.446
367 265.845
824 248.624
687 241.114
601 229.245
676 231.805
740 219.277
691 219.313
683 212.610
594 214.771
729 211.142
731 211.457
386 240.048
331 240.636
707 230.580
715 208.795
657 197.922
653 194.596
642 194.581
643 185.686
718 178.106
654 172.608
632 167.302
731 168.053
392 202.300
344 202.388
792 182.516
852 173.476
649 166.444
629 171.297
685 169.701
617 164.182
715 161.914
715 159.612
629 151.001
916 158.114
531 186.530
357 187.069
917 174.330
828 169.362
708 166.827
858 178.037
775 186.413
785 189.226
1006 191.563
789 188.906
734 186.005
906 195.309
532 223.532
387 226.899
991 214.126
841 206.903
892 204.442
782 220.375 | | 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=pearson) | | faillissementen | werklozen | faillissementen | 1 | -0.335 | werklozen | -0.335 | 1 |
Correlations for all pairs of data series with p-values | pair | Pearson r | Spearman rho | Kendall tau | faillissementen;werklozen | -0.3351 | -0.2352 | -0.1583 | p-value | (0.004) | (0.0467) | (0.0495) |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Dec/13/t1292236311hkp06j663fmhg58/1ova61292235428.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/13/t1292236311hkp06j663fmhg58/1ova61292235428.ps (open in new window) |
| | 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')
| |
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