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Data X:
7 37 20 1826 93 24 43 20 1738 61 1 0 0 192 18 10 54 27 2295 95 20 86 31 3509 137 53 181 36 6861 263 17 42 23 1801 57 19 59 30 1681 59 11 46 30 1897 44 28 77 26 2974 96 12 49 24 1946 75 21 79 30 2363 71 9 37 22 1850 101 17 92 28 3189 120 13 31 18 1486 61 14 28 22 1567 88 18 103 33 1759 58 1 2 15 1247 61 13 48 34 2779 87 4 25 18 727 25 5 16 15 1117 61 27 106 30 2809 101 5 35 25 1760 72 9 33 34 2279 56 15 45 21 1937 87 12 64 21 1800 33 16 73 25 2146 166 28 78 31 1453 95 33 63 31 2741 118 22 69 20 2112 44 12 36 28 1684 44 18 41 22 1617 46 11 59 17 2233 106 8 33 25 3122 125 26 76 24 2551 55 0 0 0 1 1 11 27 31 2137 64 9 44 14 1801 52 11 43 35 2137 49 37 104 34 2176 67 17 120 22 2390 71 11 44 34 1783 60 13 71 23 1049 33 16 78 24 2161 78 11 106 26 1364 51 15 61 23 1236 97 11 53 35 745 32 14 51 24 2410 104 22 46 31 2289 89 12 55 26 2639 59 4 14 22 658 28 11 44 21 1917 69 29 113 27 2583 75 15 55 30 2026 79 17 46 33 1911 59 15 39 11 1751 57 14 51 26 1913 68 7 31 26 1044 25 17 36 23 1177 66 7 47 38 2878 99 12 53 32 1830 63 11 38 20 2191 82 13 52 22 1331 61 14 37 26 1307 38 12 11 26 1256 35 14 45 33 1378 42 31 59 36 2311 71 15 82 25 2897 65 15 49 24 1103 38 1 6 21 340 15 16 81 19 2900 113 13 56 12 1367 74 11 105 30 1441 68 4 46 21 1681 72 15 46 34 2655 68 3 2 32 1499 44 15 51 28 2302 60 25 95 28 2540 97 6 18 21 1053 33 8 55 31 1234 71 10 48 26 927 68 16 48 29 2176 64 8 39 23 984 29 11 40 25 1551 40 3 36 22 1204 47 14 60 26 1858 58 22 114 33 2716 237 7 39 24 1207 114 7 45 24 1392 63 14 59 21 1525 53 17 59 28 1829 41 18 93 28 2383 82 15 35 25 1233 57 12 47 15 1366 59 7 36 13 953 41 25 59 36 2319 117 17 79 24 1857 70 3 14 1 223 12 13 42 24 2505 108 13 41 31 2055 83 1 8 4 747 30 8 41 21 1144 25 7 24 27 1422 57 10 22 23 1319 64 7 18 12 823 40 1 1 16 596 22 15 53 29 1644 49 2 6 26 1130 37 0 0 0 0 0 10 49 25 1082 32 5 33 21 1135 67 14 50 23 1367 45 11 64 21 1506 63 8 53 21 925 62 0 0 0 78 5 0 0 0 0 0 17 48 23 1130 44 18 90 33 1635 90 10 46 30 2122 101 10 29 23 970 39 0 1 1 778 19 17 64 29 1752 73 9 29 20 1050 43 6 27 33 2180 56 1 4 12 731 40 3 10 2 285 12 15 47 21 1834 56 8 44 28 1167 34 10 51 29 1646 54 0 0 2 256 9 0 0 0 98 9 14 38 18 1409 58 0 0 1 41 3 13 57 21 1824 63 0 0 0 42 3 2 6 4 528 16 0 0 0 0 0 8 22 29 1114 50 13 34 26 1305 38 0 0 0 81 4 0 10 4 261 14 3 16 17 1062 26 15 93 21 1279 53 12 22 22 1148 20
Names of X columns:
CH B PR P L
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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