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Data X:
299775 41 38 7 53 145 56 195838 39 32 5 86 101 56 173260 30 35 5 66 98 54 254488 31 33 5 67 132 89 104389 34 37 8 76 60 40 136084 35 29 6 78 38 25 199476 39 31 5 53 144 92 92499 34 36 6 80 5 18 224330 36 35 5 74 28 63 135781 37 38 4 76 84 44 74408 38 31 6 79 79 33 81240 36 34 5 54 127 84 14688 38 35 5 67 78 88 181633 39 38 6 54 60 55 271856 33 37 7 87 131 60 7199 32 33 6 58 84 66 46660 36 32 7 75 133 154 17547 38 38 6 88 150 53 133368 39 38 8 64 91 119 95227 32 32 7 57 132 41 152601 32 33 5 66 136 61 98146 31 31 5 68 124 58 79619 39 38 7 54 118 75 59194 37 39 7 56 70 33 139942 39 32 5 86 107 40 118612 41 32 4 80 119 92 72880 36 35 10 76 89 100 65475 33 37 6 69 112 112 99643 33 33 5 78 108 73 71965 34 33 5 67 52 40 77272 31 28 5 80 112 45 49289 27 32 5 54 116 60 135131 37 31 6 71 123 62 108446 34 37 5 84 125 75 89746 34 30 5 74 27 31 44296 32 33 5 71 162 77 77648 29 31 5 63 32 34 181528 36 33 5 71 64 46 134019 29 31 5 76 92 99 124064 35 33 5 69 0 17 92630 37 32 5 74 83 66 121848 34 33 7 75 41 30 52915 38 32 5 54 47 76 81872 35 33 6 52 120 146 58981 38 28 7 69 105 67 53515 37 35 7 68 79 56 60812 38 39 5 65 65 107 56375 33 34 5 75 70 58 65490 36 38 4 74 55 34 80949 38 32 5 75 39 61 76302 32 38 4 72 67 119 104011 32 30 5 67 21 42 98104 32 33 5 63 127 66 67989 34 38 7 62 152 89 30989 32 32 5 63 113 44 135458 37 32 5 76 99 66 73504 39 34 6 74 7 24 63123 29 34 4 67 141 259 61254 37 36 6 73 21 17 74914 35 34 6 70 35 64 31774 30 28 5 53 109 41 81437 38 34 7 77 133 68 87186 34 35 6 77 123 168 50090 31 35 8 52 26 43 65745 34 31 7 54 230 132 56653 35 37 5 80 166 105 158399 36 35 6 66 68 71 46455 30 27 6 73 147 112 73624 39 40 5 63 179 94 38395 35 37 5 69 61 82 91899 38 36 5 67 101 70 139526 31 38 5 54 108 57 52164 34 39 4 81 90 53 51567 38 41 6 69 114 103 70551 34 27 6 84 103 121 84856 39 30 6 80 142 62 102538 37 37 6 70 79 52 86678 34 31 7 69 88 52 85709 28 31 5 77 25 32 34662 37 27 7 54 83 62 150580 33 36 6 79 113 45 99611 37 38 5 30 118 46 19349 35 37 5 71 110 63 99373 37 33 4 73 129 75 86230 32 34 8 72 51 88 30837 33 31 8 77 93 46 31706 38 39 5 75 76 53 89806 33 34 5 69 49 37 62088 29 32 6 54 118 90 40151 33 33 4 70 38 63 27634 31 36 5 73 141 78 76990 36 32 5 54 58 25 37460 35 41 5 77 27 45 54157 32 28 5 82 91 46 49862 29 30 6 80 48 41 84337 39 36 6 80 63 144 64175 37 35 5 69 56 82 59382 35 31 6 78 144 91 119308 37 34 5 81 73 71 76702 32 36 7 76 168 63 103425 38 36 5 76 64 53 70344 37 35 6 73 97 62 43410 36 37 6 85 117 63 104838 32 28 6 66 100 32 62215 33 39 4 79 149 39 69304 40 32 5 68 187 62 53117 38 35 5 76 127 117 19764 41 39 7 71 37 34 86680 36 35 6 54 245 92 84105 43 42 9 46 87 93 77945 30 34 6 82 177 54 89113 31 33 6 74 49 144 91005 32 41 5 88 49 14 40248 32 33 6 38 73 61 64187 37 34 5 76 177 109 50857 37 32 8 86 94 38 56613 33 40 7 54 117 73 62792 34 40 5 70 60 75
Names of X columns:
Time_in_RFC Connected Separate age beloning totblogs Login
Type of Correlation
pearson
pearson
spearman
kendall
Chart options
Title:
R Code
par1 <- 'pearson' 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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