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Data X:
30 115 79 1 28 109 58 1 38 146 60 0 30 116 108 NA 22 68 49 NA 26 101 0 NA 25 96 121 1 18 67 1 NA 11 44 20 NA 26 100 43 1 25 93 69 0 38 140 78 0 44 166 86 NA 30 99 44 0 40 139 104 NA 34 130 63 NA 47 181 158 0 30 116 102 1 31 116 77 0 23 88 82 1 36 139 115 NA 36 135 101 1 30 108 80 0 25 89 50 1 39 156 83 NA 34 129 123 0 31 118 73 0 31 118 81 1 33 125 105 0 25 95 47 0 33 126 105 NA 35 135 94 1 42 154 44 1 43 165 114 NA 30 113 38 NA 33 127 107 1 13 52 30 NA 32 121 71 NA 36 136 84 0 0 0 0 0 28 108 59 NA 14 46 33 1 17 54 42 1 32 124 96 0 30 115 106 NA 35 128 56 1 20 80 57 0 28 97 59 1 28 104 39 0 39 59 34 NA 34 125 76 0 26 82 20 NA 39 149 91 1 39 149 115 NA 33 122 85 NA 28 118 76 0 4 12 8 0 39 144 79 0 18 67 21 NA 14 52 30 NA 29 108 76 0 44 166 101 0 21 80 94 0 16 60 27 1 28 107 92 NA 35 127 123 0 28 107 75 NA 38 146 128 NA 23 84 105 1 36 141 55 NA 32 123 56 NA 29 111 41 0 25 98 72 0 27 105 67 1 36 135 75 0 28 107 114 1 23 85 118 NA 40 155 77 NA 23 88 22 0 40 155 66 NA 28 104 69 1 34 132 105 1 33 127 116 NA 28 108 88 1 34 129 73 0 30 116 99 NA 33 122 62 0 22 85 53 NA 38 147 118 0 26 99 30 NA 35 87 100 0 8 28 49 NA 24 90 24 0 29 109 67 1 20 78 46 0 29 111 57 0 45 158 75 NA 37 141 135 0 33 122 68 NA 33 124 124 1 25 93 33 0 32 124 98 0 29 112 58 0 28 108 68 0 28 99 81 NA 31 117 131 0 52 199 110 1 21 78 37 0 24 91 130 1 41 158 93 1 33 126 118 0 32 122 39 1 19 71 13 NA 20 75 74 NA 31 115 81 0 31 119 109 NA 32 124 151 NA 18 72 51 0 23 91 28 1 17 45 40 0 20 78 56 0 12 39 27 0 17 68 37 NA 30 119 83 0 31 117 54 NA 10 39 27 NA 13 50 28 1 22 88 59 0 42 155 133 0 1 0 12 0 9 36 0 NA 32 123 106 0 11 32 23 NA 25 99 44 1 36 136 71 0 31 117 116 1 0 0 4 0 24 88 62 0 13 39 12 1 8 25 18 1 13 52 14 0 19 75 60 0 18 71 7 NA 33 124 98 0 40 151 64 NA 22 71 29 NA 38 145 32 1 24 87 25 1 8 27 16 NA 35 131 48 NA 43 162 100 0 43 165 46 NA 14 54 45 0 41 159 129 1 38 147 130 NA 45 170 136 0 31 119 59 1 13 49 25 NA 28 104 32 NA 31 120 63 0 40 150 95 NA 30 112 14 0 16 59 36 1 37 136 113 1 30 107 47 1 35 130 92 1 32 115 70 NA 27 107 19 NA 20 75 50 1 18 71 41 0 31 120 91 0 31 116 111 1 21 79 41 0 39 150 120 1 41 156 135 NA 13 51 27 NA 32 118 87 NA 18 71 25 0 39 144 131 1 14 47 45 1 7 28 29 0 17 68 58 1 0 0 4 NA 30 110 47 0 37 147 109 0 0 0 7 NA 5 15 12 NA 1 4 0 NA 16 64 37 NA 32 111 37 0 24 85 46 NA 17 68 15 1 11 40 42 NA 24 80 7 1 22 88 54 0 12 48 54 1 19 76 14 0 13 51 16 0 17 67 33 NA 15 59 32 0 16 61 21 NA 24 76 15 NA 15 60 38 1 17 68 22 1 18 71 28 NA 20 76 10 NA 16 62 31 NA 16 61 32 0 18 67 32 0 22 88 43 NA 8 30 27 NA 17 64 37 1 18 68 20 NA 16 64 32 1 23 91 0 1 22 88 5 1 13 52 26 NA 13 49 10 0 16 62 27 0 16 61 11 NA 20 76 29 0 22 88 25 0 17 66 55 1 18 71 23 NA 17 68 5 0 12 48 43 1 7 25 23 NA 17 68 34 0 14 41 36 NA 23 90 35 0 17 66 0 1 14 54 37 0 15 59 28 NA 17 60 16 NA 21 77 26 0 18 68 38 0 18 72 23 0 17 67 22 NA 17 64 30 0 16 63 16 NA 15 59 18 0 21 84 28 0 16 64 32 NA 14 56 21 1 15 54 23 NA 17 67 29 NA 15 58 50 1 15 59 12 0 10 40 21 NA 6 22 18 NA 22 83 27 0 21 81 41 0 1 2 13 NA 18 72 12 1 17 61 21 1 4 15 8 1 10 32 26 0 16 62 27 0 16 58 13 NA 9 36 16 NA 16 59 2 NA 17 68 42 NA 7 21 5 NA 15 55 37 NA 14 54 17 NA 14 55 38 NA 18 72 37 1 12 41 29 1 16 61 32 1 21 67 35 1 19 76 17 NA 16 64 20 NA 1 3 7 NA 16 63 46 NA 10 40 24 NA 19 69 40 NA 12 48 3 NA 2 8 10 0 14 52 37 NA 17 66 17 1 19 76 28 NA 14 43 19 NA 11 39 29 NA 4 14 8 NA 16 61 10 0 20 71 15 NA 12 44 15 NA 15 60 28 NA 16 64 17 0
Names of X columns:
CompendiumsReviewed FeedbackMessager BloggedComputations Geslacht
Type of Correlation
pearson
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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