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Data X:
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38 108446 0 0 13275 25 89746 0 0 6816 38 44296 0 0 1930 12 77648 0 1 8086 29 181528 0 0 10737 47 134019 0 0 8033 45 124064 0 0 7058 40 92630 0 1 6782 30 121848 0 0 5401 41 52915 0 1 6521 25 81872 0 1 10856 23 58981 0 0 2154 14 53515 0 1 6117 16 60812 0 0 5238 26 56375 0 0 4820 21 65490 0 1 5615 27 80949 0 0 4272 9 76302 0 1 8702 33 104011 0 0 15340 42 98104 0 0 8030 68 67989 0 0 9526 32 30989 0 0 1278 6 135458 0 1 4236 67 73504 0 0 3023 33 63123 0 0 7196 77 61254 0 1 3394 46 74914 0 1 6371 30 31774 0 0 1574 0 81437 0 0 9620 36 87186 0 0 6978 46 50090 0 1 4911 18 65745 0 0 8645 48 56653 0 0 8987 29 158399 0 0 5544 28 46455 0 0 3083 34 73624 0 0 6909 33 38395 0 0 3189 34 91899 0 0 6745 33 139526 0 1 16724 80 52164 0 1 4850 32 51567 0 1 7025 30 70551 0 0 6047 41 84856 0 0 7377 41 102538 0 1 9078 51 86678 0 1 4605 18 85709 0 0 3238 34 34662 0 0 8100 31 150580 0 0 9653 39 99611 0 1 8914 54 19349 0 1 786 14 99373 0 1 6700 24 86230 0 1 5788 24 30837 0 0 593 8 31706 0 0 4506 26 89806 0 0 6382 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Names of X columns:
time pop gender reviews blogs
Type of Correlation
2
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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Big Analytics Cloud Computing Center
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