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6.3 6.2 6.1 6.3 6.5 6.6 6.5 6.2 6.2 5.9 6.1 6.1 6.1 6.1 6.1 6.4 6.7 6.9 7 7 6.8 6.4 5.9 5.5 5.5 5.6 5.8 5.9 6.1 6.1 6 6 5.9 5.5 5.6 5.4 5.2 5.2 5.2 5.5 5.8 5.8 5.5 5.3 5.1 5.2 5.8 5.8 5.5 5 4.9 5.3 6.1 6.5 6.8 6.6 6.4 6.4
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R Code
gp <- function#lambda, p# { } 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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Big Analytics Cloud Computing Center
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