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Data X:
232 153 252 100 309 142 331 100 308 138 330 100 309 142 332 100 298 129 322 101.1 293 138 315 101.35 290 142 313 101.45 292 122 314 101.49 283 128 304 101.68 269 135 289 101.92 265 139 284 102.04 253 166 271 102.55 236 116 254 104.02 232 153 246 105.41 224 139 237 105.48 222 150 235 105.54 215 161 230 105.16 213 112 228 105.16 211 113 227 105.16 212 133 231 105.16 215 130 231 105.16 214 131 228 105.17 215 142 230 105.17 213 161 228 105.54 212 148 227 106.9 210 167 225 107.27 197 142 210 107.31 190 132 203 107.39 183 203 196 107.41 176 158 189 107.46 169 85 182 113.14 163 149 177 117 160 155 172 119.28 150 162 162 119.39 147 160 159 119.5 150 187 161 119.67 139 185 150 119.67 137 159 148 119.73 136 126 147 119.77 130 116 144 119.77 129 214 143 119.78 134 135 148 119.78 137 170 152 119.78 131 144 145 121.28 133 119 149 122.44 133 134 148 122.72 129 154 144 122.75 129 125 143 122.8 123 177 138 122.81 122 133 136 122.83 123 151 137 122.83 116 176 133 122.83 121 154 136 122.84 121 167 137 122.85 123 204 140 123.61 125 102 141 124.74 122 121 138 125.1 122 167 137 125.29 123 121 136 125.45 121 249 134 125.51 123 185 136 125.55
Names of X columns:
vrouw douane VlGw CPI
Type of Correlation
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='kendall') 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$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...) } bitmap(file='test1.png') pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Kendall tau rank correlations for all pairs of data series',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'pair',1,TRUE) a<-table.element(a,'tau',1,TRUE) a<-table.element(a,'p-value',1,TRUE) a<-table.row.end(a) n <- length(y[,1]) n cor.test(y[1,],y[2,],method='kendall') for (i in 1:(n-1)) { for (j in (i+1):n) { a<-table.row.start(a) dum <- paste('tau(',dimnames(t(x))[[2]][i]) dum <- paste(dum,',') dum <- paste(dum,dimnames(t(x))[[2]][j]) dum <- paste(dum,')') a<-table.element(a,dum,header=TRUE) r <- cor.test(y[i,],y[j,],method='kendall') a<-table.element(a,r$estimate) a<-table.element(a,r$p.value) a<-table.row.end(a) } } a<-table.end(a) table.save(a,file='mytable.tab')
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