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Data:
19.4 19.4 19.4 19.5 19.5 19.5 28.7 28.7 28.7 21.8 21.8 21.8 20 20 20 22.6 22.6 22.6 22.4 22.4 22.4 18.6 18.6 18.6 16.2 16.2 16.2 13.8 13.8 13.8 24.1 24.1 24.1 19.9 19.9 19.9 22.3 22.3 22.3 20.9 20.9 20.9 23.5 23.5 23.5 23.1 23.1 23.1 25.7 25.7 25.7 19.7 19.7 19.7 23.1 23.1 23.1 20.7 20.7 20.7 18 18 18 16.9 16.9 16.9 24.4 24.4 24.4 15.5 15.5 15.5 18.4 18.4 18.4 16.2 16.2 16.2 20.6 20.6 20.6 19.8 19.8 19.8
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R Code
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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