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Data X:
25 2 10 1.5 0 6 5.70 11.40 24 2 10 1.5 0 10 17.56 35.12 30 2 10 1.5 2 6 11.28 22.56 2 2 10 1.5 2 10 8.39 16.78 40 2 10 2.5 0 6 16.67 33.34 37 2 10 2.5 0 10 12.04 24.08 16 2 10 2.5 2 6 9.22 18.44 22 2 10 2.5 2 10 3.94 7.88 33 2 30 1.5 0 6 27.02 18.01 17 2 30 1.5 0 10 19.46 12.97 28 2 30 1.5 2 6 18.54 12.36 27 2 30 1.5 2 10 25.70 17.13 14 2 30 2.5 0 6 19.02 12.68 13 2 30 2.5 0 10 22.39 14.93 4 2 30 2.5 2 6 23.85 15.90 21 2 30 2.5 2 10 30.12 20.08 23 6 10 1.5 0 6 13.42 26.84 35 6 10 1.5 0 10 34.26 68.52 19 6 10 1.5 2 6 39.74 79.48 34 6 10 1.5 2 10 10.60 21.20 31 6 10 2.5 0 6 28.89 57.78 9 6 10 2.5 0 10 35.61 71.22 38 6 10 2.5 2 6 17.20 34.40 15 6 10 2.5 2 10 6.00 12.00 39 6 30 1.5 0 6 129.45 86.30 8 6 30 1.5 0 10 107.38 71.59 26 6 30 1.5 2 6 111.66 74.44 11 6 30 1.5 2 10 109.10 72.73 6 6 30 2.5 0 6 100.43 66.95 20 6 30 2.5 0 10 109.28 72.85 10 6 30 2.5 2 6 106.46 70.97 32 6 30 2.5 2 10 134.01 89.34 1 4 20 2.0 1 8 10.78 10.78 3 4 20 2.0 1 8 9.39 9.39 5 4 20 2.0 1 8 9.84 9.84 7 4 20 2.0 1 8 13.94 13.94 12 4 20 2.0 1 8 12.33 12.33 18 4 20 2.0 1 8 7.32 7.32 29 4 20 2.0 1 8 7.91 7.91 36 4 20 2.0 1 8 15.58 15.58
Names of X columns:
RUN SPEED1 TOTAL SPEED2 NUMBER2 SENS TIME T20BOLT
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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Big Analytics Cloud Computing Center
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