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Data X:
2 210907 79 94 4 179321 108 103 -4 173326 86 148 4 133131 44 90 4 258873 104 124 -1 230964 102 115 1 344297 80 108 3 174415 73 114 -1 223632 105 120 4 294424 107 124 3 325107 84 126 1 106408 33 37 -2 265769 96 120 -3 269651 106 93 -4 149112 56 95 2 152871 59 90 2 362301 76 110 -4 183167 91 138 3 277965 115 133 2 218946 76 96 2 244052 101 164 5 233328 92 102 -2 206161 75 99 -2 207176 56 114 -3 196553 41 99 2 143246 67 104 2 182192 77 138 2 194979 66 151 4 143756 105 120 4 275541 116 115 2 152299 62 98 2 193339 100 71 -4 130585 67 107 3 112611 46 73 3 148446 135 129 2 182079 124 118 -1 243060 58 104 -3 162765 68 107 1 225060 93 139 -3 133328 56 56 3 100750 83 93 3 132487 71 98 -3 317394 116 82 -4 184510 64 140 2 128423 32 120 -1 97839 25 66 3 172494 46 139 2 229242 63 119 5 351619 95 141 2 324598 113 133 -2 195838 111 98 3 199476 87 105 -2 92499 25 55 6 181633 47 73 -3 271856 109 86 3 95227 37 48 -2 118612 54 43 1 65475 16 46 2 121848 37 52 2 76302 29 68 -3 98104 55 47 -2 30989 5 41 1 31774 0 47 -4 150580 27 71 1 59382 29 24
Names of X columns:
Tot Time Comp LFB
Type of Correlation
pearson
pearson
spearman
kendall
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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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Big Analytics Cloud Computing Center
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