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48600 49200 47800 49200 48900 48600 52200 50700 50400 51900 51600 49700 49800 48000 49900 49600 49200 47600 51400 51000 49800 50900 51400 51000 52700 51600 51900 53000 51600 51400 51000 51600 49400 51100 52800 49000
minimum value of shape parameter
maximum value of shape parameter
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R Code
library(MASS) PPCCGamma <- function(shape, rate, x) { x <- sort(x) pp <- ppoints(x) cor(qgamma(pp, shape=shape, rate=rate), 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 <- par1*10 par2h <- par2*10 sortx <- sort(x) c <- array(NA,dim=c(par2h)) for (i in par1h:par2h) { c[i] <- cor(qgamma(ppoints(x), shape=i/10,rate=2),sortx) } bitmap(file='test1.png') plot((par1h:par2h)/10,c[par1h:par2h],xlab='shape',ylab='correlation',main='PPCC Plot - Gamma') dev.off() f<-fitdistr(x, 'gamma') f$estimate f$sd xlab <- paste('Gamma(shape=',round(f$estimate[[1]],2)) xlab <- paste(xlab,', rate=') xlab <- paste(xlab,round(f$estimate[[2]],2)) xlab <- paste(xlab,')') bitmap(file='test2.png') qqplot(qgamma(ppoints(x), shape=f$estimate[[1]], rate=f$estimate[[2]]), x, main='QQ plot (Gamma)', 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,'rate',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')
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Big Analytics Cloud Computing Center
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