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Data:
-0.07114 0.9168 1.316 0.2179 0.3155 0.8239 2.218 0.8239 0.2059 0.2059 1.316 -0.2905 0.7095 -0.0664 0.3155 1.824 0.8239 -1.909 1.316 1.218 -0.6845 0.3155 -0.6845 1.316 -0.1761 1.218 -0.6845 1.332 -0.1928 -1.575 -1.794 0.8072 0.4252 -0.558 0.2059 -0.1761 -0.1808 -0.5748 2.316 -1.193 0.2059 -1.066 -0.9085 -0.7989 -0.2905 0.3155 -0.8918 -2.684 0.2059 -0.3025 -0.3025 -3.575 -0.1808 -2.684 0.2179 1.824 0.7095 -0.6845 -0.3025 1.332 0.3155 0.8239 -0.6845 -1.465 1.71 -1.29 -1.799 1.218 0.2179 -2.188 -2.684 -2.684 0.9216 -0.1761 0.3155 -0.7821 0.9336 2.425 0.3155 -2.066 0.3155 1.316 1.316 3.807 0.4132 2.316 -0.1761 1.824 0.9289 -0.6845 1.316 0.3155 0.2059 0.2179 0.3155 1.807 1.413 -0.7941 1.917 -0.6845 -3.193 0.2179 0.4132 0.7095 0.7095 -0.6845 0.3155 0.8239 -2.684 -0.2905 -1.672 3.71 0.8239 0.3155 0.4132 -0.1928 -1.684 -0.2905 -0.7821 0.3155 -0.6845 0.2059 -0.1761 0.7095 0.3155 0.2179 -0.2905 -1.169 0.7095 2.201 -1.274 -3.066 0.7095 0.6975 -1.794 1.304 0.2059 -2.29 -1.176 0.3155 -2.684 1.316 -1.684 3.201 -0.5748 0.3155 -1.672 -0.7941 0.7095 -0.6845 -2.782 -0.6845 0.8072 -2.684 1.442 2.316 0.8192 2.316 -2.188 -1.193 0.2011 -1.066 0.3155 -2.684 2.048
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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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1 seconds
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Big Analytics Cloud Computing Center
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