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Data X:
210907 30 94 112285 144 145 179321 30 103 101193 135 132 149061 26 93 116174 84 84 237213 38 123 66198 130 127 173326 44 148 71701 82 78 133131 30 90 57793 60 60 258873 40 124 80444 131 131 324799 47 168 97668 140 133 230964 30 115 133824 151 150 236785 31 71 101481 91 91 344297 30 108 67654 119 118 174724 34 120 69112 123 119 174415 31 114 82753 90 89 223632 33 120 72654 113 108 294424 33 124 101494 175 162 325107 36 126 79215 96 92 106408 14 37 31081 41 41 96560 17 38 22996 47 47 265769 32 120 83122 126 120 269651 30 93 70106 105 105 149112 35 95 60578 80 79 152871 28 90 79892 73 70 362301 34 110 100708 68 67 183167 39 138 82875 127 127 277965 39 133 139077 154 152 218946 29 96 80670 112 109 244052 44 164 143558 137 133 341570 21 78 117105 135 123 233328 28 102 120733 230 230 206161 28 99 73107 71 68 311473 38 129 132068 147 147 207176 32 114 87011 105 101 196553 29 99 95260 107 108 143246 27 104 106671 116 114 182192 40 138 70054 89 88 194979 40 151 74011 84 83 167488 28 72 83737 113 113 143756 34 120 69094 120 118 275541 33 115 93133 110 110 152299 33 98 61370 78 76 193339 35 71 84651 145 141 130585 29 107 95364 91 91 112611 20 73 26706 48 48 148446 37 129 126846 150 144 182079 33 118 102860 181 168 243060 29 104 111813 121 117 162765 28 107 120293 99 100 85574 21 36 24266 40 37 225060 41 139 109825 87 87 133328 20 56 40909 66 64 100750 30 93 140867 58 58 101523 22 87 61056 77 76 243511 42 110 101338 130 129 152474 32 83 65567 101 101 132487 36 98 40735 120 89 317394 31 82 91413 195 193 244749 33 115 76643 106 101 184510 40 140 110681 83 82 128423 38 120 92696 37 36 97839 24 66 94785 77 75 172494 43 139 86687 144 131 229242 31 119 91721 95 90 351619 40 141 115168 169 166 324598 37 133 135777 134 133 195838 31 98 102372 197 196 254488 39 117 103772 140 136 199476 32 105 135400 125 123 92499 18 55 21399 21 21 224330 39 132 130115 167 163 181633 30 73 64466 96 96 271856 37 86 54990 151 151 95227 32 48 34777 23 23 98146 17 48 27114 21 14 118612 12 43 30080 90 87 65475 13 46 69008 60 56 108446 17 65 46300 26 25 121848 17 52 30594 41 41 76302 20 68 30976 35 33 98104 17 47 25568 68 68 30989 17 41 4154 6 6 31774 17 47 4143 0 0 150580 22 71 45588 41 39 54157 15 30 18625 38 37 59382 12 24 26263 47 47 84105 17 63 20055 34 34
Names of X columns:
time_in_rfc compendiums_reviewed feedback_messages_p120 totsize tothyperlinks totblogs
Type of Correlation
kendall
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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