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10 15 14 14 8 19 17 18 10 15 16 12 13 10 14 15 20 9 12 13 16 12 14 15 19 16 16 14 14 14 13 18 15 15 15 13 14 15 14 19 16 16 12 10 11 13 14 11 11 16 9 16 19 13 15 14 15 11 14 15 17 16 13 15 14 15 14 12 12 15 17 13 5 7 10 15 9 9 15 14 11 18 20 20 16 15 14 13 18 14 12 9 19 13 12 14 6 14 11 11 14 12 19 13 14 17 12 16 15 15 15 16 15 12 13 14 17 14 14 14 15 11 11 16 12 12 19 18 16 16 13 11 10 14 14 14 16 10 16 7 16 15 17 11 11 10 13 14 13 13 12 10 15 6 15 15 11 14 14 16 12 15 20 12 9 13 15 19 11 11 17 15 14 15 11 12 15 16 16
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R Code
par3 <- '0.01' 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,signif(as.matrix(hd[i])[1,1],6)) a<-table.element(a,signif(as.matrix(attr(hd,'se')[i])[1,1],6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')
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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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