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Data X:
260.6 7.5 277 7.7 291.6 8.3 260.6 7.5 275.4 7.8 291.6 8.3 275.3 7.9 275.4 7.8 231.7 6.6 275.3 7.9 238.8 7 231.7 6.6 274.2 8.2 238.8 7 277.8 8.2 274.2 8.2 299.1 9.1 277.8 8.2 286.6 9 299.1 9.1 232.3 7.1 286.6 9 294.1 8.9 232.3 7.1 267.5 8.5 294.1 8.9 309.7 9.8 267.5 8.5 280.7 8.8 309.7 9.8 287.3 9.2 280.7 8.8 235.7 7.4 287.3 9.2 256.4 8.3 235.7 7.4 289 9.7 256.4 8.3 290.8 9.7 289 9.7 321.9 10.8 290.8 9.7 291.8 9.8 321.9 10.8 241.4 7.9 291.8 9.8 295.5 9.8 241.4 7.9 258.2 9 295.5 9.8 306.1 10.5 258.2 9 281.5 9.5 306.1 10.5 283.1 9.7 281.5 9.5 237.4 8.1 283.1 9.7 274.8 10.1 237.4 8.1 299.3 11.1 274.8 10.1 300.4 11.2 299.3 11.1 340.9 12.6 300.4 11.2 318.8 12.2 340.9 12.6 265.7 9.9 318.8 12.2 322.7 11.8 265.7 9.9 281.6 11.1 322.7 11.8 323.5 12.6 281.6 11.1 312.6 11.9 323.5 12.6 310.8 11.9 312.6 11.9 262.8 10 310.8 11.9 273.8 10.8 262.8 10 320 12.9 273.8 10.8 310.3 12.5 320 12.9 342.2 13.8 310.3 12.5 320.1 13.1 342.2 13.8 265.6 10.5 320.1 13.1 327 12.9 265.6 10.5 300.7 12.9 327 12.9 346.4 14.4 300.7 12.9 317.3 12.7 346.4 14.4 326.2 13.3 317.3 12.7 270.7 11 326.2 13.3 278.2 11.9 270.7 11 324.6 14.1 278.2 11.9 321.8 14.4 324.6 14.1 343.5 14.9 321.8 14.4 354 15.7 343.5 14.9 278.2 12 354 15.7 330.2 14.3 278.2 12 307.3 14.2 330.2 14.3 375.9 17.4 307.3 14.2 335.3 15.1 375.9 17.4 339.3 15.3 335.3 15.1 280.3 12.6 339.3 15.3 293.7 14 280.3 12.6 341.2 16.6 293.7 14 345.1 16.7 341.2 16.6 368.7 17.6 345.1 16.7 369.4 18.3 368.7 17.6 288.4 13.6 369.4 18.3 341 15.8 288.4 13.6 319.1 16.1 341 15.8 374.2 18.6 319.1 16.1 344.5 17.3 374.2 18.6 337.3 17 344.5 17.3 281 13.9 337.3 17 282.2 15.2 281 13.9 321 17.8 282.2 15.2 325.4 18 321 17.8 366.3 19.4 325.4 18 380.3 21.8 366.3 19.4 300.7 16.2 380.3 21.8 359.3 19.2 300.7 16.2 327.6 19.5 359.3 19.2 383.6 22 327.6 19.5 352.4 20 383.6 22 329.4 19.2 352.4 20 294.5 16.9 329.4 19.2 333.5 20 294.5 16.9 334.3 20.4 333.5 20 358 21.8 334.3 20.4 396.1 25 358 21.8 387 25.8 396.1 25 307.2 19.4 387 25.8 363.9 22.6 307.2 19.4 344.7 24.1 363.9 22.6 397.6 26.9 344.7 24.1 376.8 24.9 397.6 26.9 337.1 23.3 376.8 24.9 299.3 20.3 337.1 23.3 323.1 22.3 299.3 20.3 329.1 23.7 323.1 22.3 347 24.3 329.1 23.7 462 31.7 347 24.3 436.5 32.2 462 31.7 360.4 25.4 436.5 32.2 415.5 28.6 360.4 25.4 382.1 28.7 415.5 28.6 432.2 30.9 382.1 28.7 424.3 31.4 432.2 30.9 386.7 29.1 424.3 31.4 354.5 26.3 386.7 29.1 375.8 28.9 354.5 26.3 368 28.9 375.8 28.9 402.4 31 368 28.9 426.5 33.4 402.4 31 433.3 35.9 426.5 33.4 338.5 25.8 433.3 35.9 416.8 31.2 338.5 25.8 381.1 31.7 416.8 31.2 445.7 36.2 381.1 31.7 412.4 32 445.7 36.2 394 32.1 412.4 32 348.2 28.1 394 32.1 380.1 31.1 348.2 28.1 373.7 31.9 380.1 31.1 393.6 32 373.7 31.9 434.2 36.6 393.6 32 430.7 38.1 434.2 36.6 344.5 28.1 430.7 38.1 411.9 32.9 344.5 28.1 370.5 30.7 411.9 32.9 437.3 35.4 370.5 30.7 411.3 33.7 437.3 35.4 385.5 31.6 411.3 33.7 341.3 27.9 385.5 31.6 384.2 32.2 341.3 27.9 373.2 32.3 384.2 32.2 415.8 35.3 373.2 32.3 448.6 37.2 415.8 35.3 454.3 39.6 448.6 37.2 350.3 28.4 454.3 39.6 419.1 33.9 350.3 28.4 398 33.7 419.1 33.9 456.1 38.3 398 33.7 430.1 34.6 456.1 38.3 399.8 32.7 430.1 34.6 362.7 29.5 399.8 32.7 384.9 32 362.7 29.5 385.3 33.2 384.9 32 432.3 36.7 385.3 33.2 468.9 38.6 432.3 36.7 442.7 38.1 468.9 38.6 370.2 29.8 442.7 38.1 439.4 35.6 370.2 29.8 393.9 33.2 439.4 35.6 468.7 38.9 393.9 33.2 438.8 34.8 468.7 38.9 430.1 37.2 438.8 34.8 366.3 29.7 430.1 37.2 391 32.2 366.3 29.7 380.9 32.1 391 32.2 431.4 36.3 380.9 32.1 465.4 38.4 431.4 36.3 471.5 40.8 465.4 38.4 387.5 31.3 471.5 40.8 446.4 36.2 387.5 31.3 421.5 35.1 446.4 36.2 504.8 44.1 421.5 35.1 492.1 39.3 504.8 44.1 421.3 34.1 492.1 39.3 396.7 32.4 421.3 34.1 428 36.3 396.7 32.4 421.9 36.8 428 36.3 465.6 40.5 421.9 36.8 525.8 46 465.6 40.5 499.9 43.9 525.8 46 435.3 37.2 499.9 43.9 479.5 40.7 435.3 37.2 473 42 479.5 40.7 554.4 49.2 473 42 489.6 42.3 554.4 49.2 462.2 40.8 489.6 42.3 420.3 37.6 462.2 40.8
Names of X columns:
Y[t] X[t] Y[t-1] X[t-1]
Type of Correlation
FALSE
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='kendall') 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$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...) } bitmap(file='test1.png') pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Kendall tau rank correlations for all pairs of data series',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'pair',1,TRUE) a<-table.element(a,'tau',1,TRUE) a<-table.element(a,'p-value',1,TRUE) a<-table.row.end(a) n <- length(y[,1]) n cor.test(y[1,],y[2,],method='kendall') for (i in 1:(n-1)) { for (j in (i+1):n) { a<-table.row.start(a) dum <- paste('tau(',dimnames(t(x))[[2]][i]) dum <- paste(dum,',') dum <- paste(dum,dimnames(t(x))[[2]][j]) dum <- paste(dum,')') a<-table.element(a,dum,header=TRUE) r <- cor.test(y[i,],y[j,],method='kendall') a<-table.element(a,r$estimate) a<-table.element(a,r$p.value) a<-table.row.end(a) } } a<-table.end(a) table.save(a,file='mytable.tab')
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