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Data:
338.3622951 617.8622951 261.8622951 490.1622951 546.8622951 389.5622951 441.5622951 346.5622951 393.1622951 567.3622951 461.7622951 531.1622951 486.9622951 495.9622951 347.6622951 493.1622951 550.3622951 470.7622951 414.0622951 470.4622951 371.1622951 535.8622951 506.2622951 631.2622951 526.0622951 560.7622951 400.7622951 640.5622951 605.3622951 624.9622951 473.1622951 567.5622951 449.5622951 605.5622951 485.5622951 739.4622951 415.1622951 571.2622951 408.6622951 540.2622951 594.1622951 423.7622951 425.5622951 416.5622951 534.0622951 757.6622951 467.4622951 609.2622951 504.1622951 739.6622951 716.2622951 476.8622951 708.1622951 556.2622951 507.1622951 484.8622951 441.9622951 423.9622951 386.7622951 354.6622951 195.8622951
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R Code
gp <- function(lambda, p) { (p^lambda-(1-p)^lambda)/lambda } sortx <- sort(x) c <- array(NA,dim=c(201)) for (i in 1:201) { if (i != 101) c[i] <- cor(gp(ppoints(x), lambda=(i-101)/100),sortx) } bitmap(file='test1.png') plot((-100:100)/100,c[1:201],xlab='lambda',ylab='correlation',main='PPCC Plot - Tukey lambda') grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Tukey Lambda - Key Values',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Distribution (lambda)',1,TRUE) a<-table.element(a,'Correlation',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Approx. Cauchy (lambda=-1)',header=TRUE) a<-table.element(a,c[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Exact Logistic (lambda=0)',header=TRUE) a<-table.element(a,(c[100]+c[102])/2) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Approx. Normal (lambda=0.14)',header=TRUE) a<-table.element(a,c[115]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'U-shaped (lambda=0.5)',header=TRUE) a<-table.element(a,c[151]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Exactly Uniform (lambda=1)',header=TRUE) a<-table.element(a,c[201]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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