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Data:
5.44 18.78 35.97 53.71 65.86 78.08 89.77 94.08 96.07 97.42

minimum value of shape parameter


maximum value of shape parameter


Chart options



R Code
par2 <- '90' par1 <- '1' library(MASS) PPCCWeibull <- function(shape, scale, x) { x <- sort(x) pp <- ppoints(x) cor(qweibull(pp, shape=shape, scale=scale), x) } par1 <- as.numeric(par1) par2 <- as.numeric(par2) if (par1 < 0.1) par1 <- 0.1 if (par1 > 50) par1 <- 50 if (par2 < 0.1) par2 <- 0.1 if (par2 > 50) par2 <- 50 par1h <- par110 par2h <- par210 sortx <- sort(x) c <- array(NA,dim=c(par2h)) for (i in par1h:par2h) { c[i] <- cor(qweibull(ppoints(x), shape=i/10,scale=2),sortx) } bitmap(file='test1.png') plot((par1h:par2h)/10,c[par1h:par2h],xlab='shape',ylab='correlation',main='PPCC Plot - Weibull') dev.off() f<-fitdistr(x, 'weibull') f$estimate f$sd xlab <- paste('Weibull(shape=',round(f$estimate[[1]],2)) xlab <- paste(xlab,', scale=') xlab <- paste(xlab,round(f$estimate[[2]],2)) xlab <- paste(xlab,')') bitmap(file='test2.png') qqplot(qweibull(ppoints(x), shape=f$estimate[[1]], scale=f$estimate[[2]]), x, main='QQ plot (Weibull)', xlab=xlab ) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Parameter',1,TRUE) a<-table.element(a,'Estimated Value',1,TRUE) a<-table.element(a,'Standard Deviation',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'shape',header=TRUE) a<-table.element(a,f$estimate[1]) a<-table.element(a,f$sd[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'scale',header=TRUE) a<-table.element(a,f$estimate[2]) a<-table.element(a,f$sd[2]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center