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Data X:
-15 -7 55 23 39 24 -8 -2 19 4 -22 11 -8 -7 -1 54 20 19 23 -12 -3 18 6 -15 9 -1 -6 0 52 20 14 19 -10 0 20 5 -16 13 1 -6 -3 55 22 15 25 -11 -4 21 4 -22 12 -1 2 4 56 25 7 21 -13 -3 18 5 -21 5 2 -4 2 54 22 12 19 -10 -3 19 5 -11 13 2 -4 3 53 26 12 20 -10 -3 19 4 -10 11 1 -8 0 59 27 14 20 -11 -4 19 3 -6 8 -1 -10 -10 62 41 9 17 -11 -5 21 2 -8 8 -2 -16 -10 63 29 8 25 -11 -5 19 3 -15 8 -2 -14 -9 64 33 4 19 -10 -6 19 2 -16 8 -1 -30 -22 75 39 7 13 -13 -10 17 -1 -24 0 -8 -33 -16 77 27 3 15 -12 -11 16 0 -27 3 -4 -40 -18 79 27 5 15 -13 -13 16 -2 -33 0 -6 -38 -14 77 25 0 13 -15 -12 17 1 -29 -1 -3 -39 -12 82 19 -2 11 -16 -13 16 -2 -34 -1 -3 -46 -17 83 15 6 9 -18 -12 15 -2 -37 -4 -7 -50 -23 81 19 11 2 -17 -15 16 -2 -31 1 -9 -55 -28 78 23 9 -2 -18 -14 16 -6 -33 -1 -11 -66 -31 79 23 17 -4 -20 -16 16 -4 -25 0 -13 -63 -21 79 7 21 -2 -22 -16 18 -2 -27 -1 -11 -56 -19 73 1 21 1 -17 -12 19 0 -21 6 -9 -66 -22 72 7 41 -13 -19 -16 16 -5 -32 0 -17 -63 -22 67 4 57 -11 -18 -15 16 -4 -31 -3 -22 -69 -25 67 -8 65 -14 -26 -17 16 -5 -32 -3 -25 -69 -16 50 -14 68 -4 -19 -15 18 -1 -30 4 -20 -72 -22 45 -10 73 -9 -23 -14 16 -2 -34 1 -24 -69 -21 39 -11 71 -5 -21 -15 15 -4 -35 0 -24 -67 -10 39 -10 71 -4 -27 -14 15 -1 -37 -4 -22 -64 -7 37 -8 70 -8 -27 -16 16 1 -32 -2 -19 -61 -5 30 -8 69 -1 -21 -11 18 1 -28 3 -18 -58 -4 24 -7 65 -2 -22 -14 16 -2 -26 2 -17 -47 7 27 -8 57 -1 -24 -12 19 1 -24 5 -11 -44 6 19 -4 57 8 -21 -11 19 1 -27 6 -11 -42 3 19 3 57 8 -21 -13 18 3 -26 6 -12 -34 10 25 -5 55 6 -22 -12 17 3 -27 3 -10 -38 0 16 -4 65 7 -25 -12 19 1 -27 4 -15 -41 -2 20 5 65 2 -21 -10 22 1 -24 7 -15 -38 -1 25 3 64 3 -26 -12 19 0 -28 5 -15 -37 2 34 6 60 0 -27 -11 19 2 -23 6 -13 -22 8 39 10 43 5 -22 -10 16 2 -23 1 -8 -37 -6 40 16 47 -1 -22 -12 18 -1 -29 3 -13 -36 -4 38 11 40 3 -20 -12 20 1 -25 6 -9 -25 4 42 10 31 4 -21 -11 17 0 -24 0 -7 -15 7 46 21 27 8 -16 -12 17 1 -20 3 -4 -17 3 48 18 24 10 -17 -9 17 1 -22 4 -4 -19 3 51 20 23 14 -19 -6 20 3 -24 7 -2 -12 8 55 18 17 15 -20 -7 21 2 -27 6 0 -17 3 52 23 16 9 -20 -7 19 0 -25 6 -2 -21 -3 55 28 15 8 -20 -10 18 0 -26 6 -3 -10 4 58 31 8 10 -19 -8 20 3 -24 6 1 -19 -5 72 38 5 5 -20 -11 17 -2 -26 2 -2 -14 -1 70 27 6 4 -25 -12 15 0 -22 2 -1 -8 5 70 21 5 8 -25 -11 17 1 -20 2 1 -16 0 63 31 12 8 -22 -11 18 -1 -26 3 -3 -14 -6 66 31 8 10 -19 -9 20 -2 -22 -1 -4 -30 -13 65 29 17 8 -20 -9 19 -1 -29 -4 -9 -33 -15 55 24 22 10 -18 -12 20 -1 -30 4 -9 -37 -8 57 27 24 -8 -17 -10 22 1 -26 5 -7 -47 -20 60 36 36 -6 -17 -10 20 -2 -30 3 -14
Names of X columns:
EconomischeSituatieBelgiëVooraf EconomischeSituatieBelgiëToekomst OntwikkelingConsumptieprijzenVooraf OntwikkelingConsumptieprijzenToekomst VoorzuitichtenWerkloosheid TijdstipGunstigAankopen VooruitzichtenAankopen FinanciëleSituatieVerleden FinanciëleSituatieNu FinanciëleSituatieToekomst SparenNu SparenToekomst Consumentenvertrouwen
Type of Correlation
pearson
pearson
spearman
kendall
Chart options
Title:
R Code
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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