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Data:
17.1 13.4 15.3 14 9.7 13.7 13.7 12.5 9.8 7 -1.9 -2.9 -6.8 -10.4 -17.2 -19.8 -16.8 -23.2 -21.7 -17.6 -13 -12.6 -4 -0.2 3.1 6.5 19.2 26.6 26.6 31.4 31.2 26.4 20.7 20.7 15 13.3 8.7 10.2 4.3 -0.1 -4.6 -3.9 -3.5 -3.4 -2.5 -1.1 0.3 -0.9 3.6 2.7 -0.2 -1 5.8 6.4 9.6 13.2 10.6 10.9 12.9 15.9 12.2 9.1 9 17.4 14.7 17 13.7 9.5 14.8 13.6 12.6 8.9 10.2 12.7 16 10.4 9.9 9.5 8.6 10 3.5 -4.2 -4.4 -1.5 -0.1 0.8 -2.4 -1.2 0.2 -1.9 -1.6 -4.2 -2.2 6.2 5.7 3.1 1.1 -0.9 0.1 -4 -4 -5.3 -8 -6.3 -3.6 -3.5 -5.1 -3.3
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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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