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Data X:
286602 326011 20366 2.00 283042 328282 22782 2.00 276687 317480 19169 2.00 277915 317539 13807 2.00 277128 313737 29743 2.00 277103 312276 25591 2.00 275037 309391 29096 2.00 270150 302950 26482 2.00 267140 300316 22405 2.00 264993 304035 27044 2.00 287259 333476 17970 2.00 291186 337698 18730 2.00 292300 335932 19684 2.00 288186 323931 19785 2.00 281477 313927 18479 2.00 282656 314485 10698 2.21 280190 313218 31956 2.25 280408 309664 29506 2.25 276836 302963 34506 2.45 275216 298989 27165 2.50 274352 298423 26736 2.50 271311 301631 23691 2.64 289802 329765 18157 2.75 290726 335083 17328 2.93 292300 327616 18205 3.00 278506 309119 20995 3.17 269826 295916 17382 3.25 265861 291413 9367 3.39 269034 291542 31124 3.50 264176 284678 26551 3.50 255198 276475 30651 3.65 253353 272566 25859 3.75 246057 264981 25100 3.75 235372 263290 25778 3.90 258556 296806 20418 4.00 260993 303598 18688 4.00 254663 286994 20424 4.00 250643 276427 24776 4.00 243422 266424 19814 4.00 247105 267153 12738 4.00 248541 268381 31566 4.00 245039 262522 30111 4.00 237080 255542 30019 4.00 237085 253158 31934 4.00 225554 243803 25826 4.00 226839 250741 26835 4.00 247934 280445 20205 4.18 248333 285257 17789 4.25 246969 270976 20520 4.25 245098 261076 22518 3.97 246263 255603 15572 3.42 255765 260376 11509 2.75 264319 263903 25447 2.31 268347 264291 24090 2.00 273046 263276 27786 1.66 273963 262572 26195 1.31 267430 256167 20516 1.09 271993 264221 22759 1.00 292710 293860 19028 1.00 295881 300713 16971 1.00
Names of X columns:
nwwmb nwwvb inpwb vrv
Type of Correlation
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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Big Analytics Cloud Computing Center
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