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Data:
3.9 5.9 5.7 3.6 4.9 5.3 8.7 6.8 8.9 9.6 11.2 9.9 9.3 9.2 9.4 12.7 13.6 16.1 14.8 14.1 13.2 8.7 4.9 -1.3 -3.9 -6 -6.6 -8.7 -11.6 -14.6 -12.9 -13.8 -14.1 -13.2 -10.4 -3.3 1 3.1 4.5 1.9 3.9 7 5.6 8.1 6.1 8 6.5 5.6 4.8 5.1 7.8 10.3 8.6 6.8 4.9 5.4 5.5 4.7 4.2 5 5 6 2.9 3.6 5.1 2.9 4.7 3 5 2.6 3.2 2.4 3.2 2.6 2.4 2.1 2.7 4.4 4.3 4.2 5.5 8.8 10.1 7 5.7 5.2 5.5 7.3 5.9 7.1 6.9 6.7 4.7 6.7 8.5 2.1 -0.9 -4.7 4.8 2.6 1.7 -1.8 0.2 1.9 3.2 3.1 4.2 16.2 18.3 21.6 12.6 9.8 10.6 13 9.7 7.9 3.3 3.4 0.4
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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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