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Data:
0.224565646 0.261571480 0.253029834 0.033938060 0.353208554 0.033295045 0.002171707 0.084136132 0.077468368 0.010160325 0.079746191 0.263485597 0.460389066 0.132348066 0.529154319 0.032287005 0.472190992 0.037985170 0.019795866 0.053763887 0.086771175 0.143764004 0.202780264 0.006932185 0.124637036 0.116166293 0.037363442 0.416532177 0.612491026 0.012781084 0.163992436 0.212717925 0.092409609 0.150134816 0.047430792 0.022017328 0.350262865 0.013821921 0.578796918 0.030264300 0.090627282 0.029354226 0.182663201 0.372085552 0.235142217 0.311617946 0.030548270 0.068424450 0.043757662 0.238109173 0.465951209 0.127494709 0.010810575 0.230141979 0.426687450 0.175605499 0.005595384 0.203565169 0.236888269 0.153586896 0.027445414 0.026240968 0.299075759 0.171469487 0.016355307 0.220064442 0.137054994 0.034683689 0.085767702 0.119746590 0.223347602 0.026601623 0.063485064 0.467803972 0.012650088 0.048496183 0.047170846 0.043196485 0.095073370 0.538513979 0.045034181 0.427235474 0.289835816 0.150884924 0.176887675 0.369202741 0.178461483 0.077501113 0.281105892 0.051375864 0.357311398 0.561861189 0.028342902 0.326209843 0.303994601 0.020530542 0.278139180 0.582716856 0.071720238 0.237546024
minimum value of shape1 parameter
maximum value of shape1 parameter
minimum value of shape2 parameter
maximum value of shape2 parameter
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R Code
library(MASS) PPCCBeta <- function(shape1, shape2, x) { x <- sort(x) pp <- ppoints(x) cor(qbeta(pp, shape1=shape1, shape2=shape2), x) } par1 <- as.numeric(par1) par2 <- as.numeric(par2) par3 <- as.numeric(par3) par4 <- as.numeric(par4) if (par1 < 0.1) par1 <- 0.1 if (par1 > 10) par1 <- 10 if (par2 < 0.1) par2 <- 0.1 if (par2 > 10) par2 <- 10 if (par3 < 0.1) par3 <- 0.1 if (par3 > 10) par3 <- 10 if (par4 < 0.1) par4 <- 0.1 if (par4 > 10) par4 <- 10 par1h <- par1*10 par2h <- par2*10 par3h <- par3*10 par4h <- par4*10 sortx <- sort(x) c <- array(NA,dim=c(par2h,par4h)) for (i in par1h:par2h) { for (j in par3h:par4h) { c[i,j] <- cor(qbeta(ppoints(x), shape1=i/10,shape2=j/10),sortx) } } bitmap(file='test1.png') filled.contour((par1h:par2h)/10,(par3h:par4h)/10,c[par1h:par2h,par3h:par4h],xlab='shape1',ylab='shape2',main='PPCC Contour Plot - Beta') dev.off() xbar <- mean(x) xvar <- var(x) (a <- (xbar*(1-xbar)/xvar - 1)*xbar) (b <- (1-xbar)*a) (f<-fitdistr(x, 'beta',list(shape1=a,shape2=b))) xlab <- paste('Beta(shape1=',round(f$estimate[[1]],2)) xlab <- paste(xlab,', shape2=') xlab <- paste(xlab,round(f$estimate[[2]],2)) xlab <- paste(xlab,')') bitmap(file='test2.png') myser <- qbeta(ppoints(x), shape1=f$estimate[[1]], shape2=f$estimate[[2]]) qqplot(myser, x, main='QQ plot (Beta)', 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,'shape1',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,'shape2',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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