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Data:
8.9 9.2 12.8 11.1 11.2 13.1 12.6 10 12.3 12.5 11.4 11.5 10.4 11 15 12.7 11.6 13.9 12.6 11.2 15.8 15.3 14 14.6 11.5 12.8 16.2 12.8 13.5 12.5 13.2 12 14.2 17.5 13.8 13.9 11.3 12.1 16.2 11.6 12.5 15.6 12.3 12 12.1 13.9 12.3 10.5 14.2 13.2 13.7 14.2 15.3 16.3 15.1 13.4 14 15.5 12.5 12.9 12.9 13.4 15 14.4 14 15.2 15 12.4 18.7 20.6 17.3 11.4
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R Code
par3 <- '0.09' par2 <- '0.99' par1 <- '0.01' par1 <- as(par1,'numeric') par2 <- as(par2,'numeric') par3 <- as(par3,'numeric') library(Hmisc) myseq <- seq(par1, par2, par3) hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE) bitmap(file='test1.png') plot(myseq,hd,col=2,main=main,xlab=xlab,ylab=ylab) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Harrell-Davis Quantiles',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'quantiles',header=TRUE) a<-table.element(a,'value',header=TRUE) a<-table.element(a,'standard error',header=TRUE) a<-table.row.end(a) length(hd) for (i in 1:length(hd)) { a<-table.row.start(a) a<-table.element(a,as(labels(hd)[i],'numeric'),header=TRUE) a<-table.element(a,as.matrix(hd[i])[1,1]) a<-table.element(a,as.matrix(attr(hd,'se')[i])[1,1]) 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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