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Data:
12.8 12.1 11.4 11.4 10.6 10.4 10.9 11.6 13.3 15.2 17.4 19.1 19.9 19.4 18.2 15.8 13.5 12.1 10.3 8.8 8.2 6.8 5.9 4.9 3.9 3.6 2.8 4 4.2 4.2 4.8 4 3.8 4 3.7 4 4.6 4.6 4.6 4.5 4.1 4.1 4.4 4.2 4.4 3.2 2.8 1.7 -0.2 -2.9 -5.2 -5.3 -4.8 -2.2 -0.8 -1.1 -1.5 -2 -2.8 -3.4 -4.1 -5.5 -8.6 -7.6 -8.6 -8.7 -4.6 -4.3 -1.5 1.2 1.8 0
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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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