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Data X:
1972 33907 71433 152 74272 99 765 1973 35981 53655 99 78867 128 1371 1974 36588 70556 92 80176 57 1880 1975 16967 74702 138 36541 95 232 1976 25333 61201 106 55107 205 230 1977 21027 686 95 45527 51 828 1978 21114 87586 145 46001 59 1833 1979 28777 6615 181 62854 194 906 1980 35612 89725 190 78112 27 1781 1981 24183 40420 150 52653 9 1264 1982 22262 49569 186 48467 24 1123 1983 20637 13963 174 44873 189 1461 1984 29948 62508 151 65605 37 820 1985 22093 90901 112 48016 81 107 1986 36997 89418 143 81110 72 1349 1987 31089 83237 120 68019 81 870 1988 19477 22183 169 42198 90 1471 1989 31301 24346 135 68531 216 731 1990 18497 74341 161 40071 216 1945 1991 30142 24188 98 65849 13 521 1992 21326 11781 142 46362 153 1920 1993 16779 23072 190 36313 185 1924 1994 38068 49119 169 83521 131 100 1995 29707 67776 130 64932 136 34 1996 35016 86910 160 76730 182 325 1997 26131 69358 176 56982 139 1677 1998 29251 16144 111 63793 42 1779 1999 22855 77863 165 49740 213 477 2000 31806 89070 117 69447 184 1007 2001 34124 34790 122 74708 44 1527
Names of X columns:
Jaar Omzet Uitgaven Prijs Gemiddeld_Budget Consumentevertrouwen Uitgaven
Type of Correlation
pearson
pearson
spearman
kendall
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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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