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Data:
0.75 0.75 0.77 0.78 0.79 1.01 1.16 1.14 1.12 1.1 1.1 1.1 1.1 1.09 1.09 1.1 1.1 1.17 1.15 1.04 0.94 0.88 0.85 0.85 0.85 0.84 0.83 0.8 0.78 1.02 1.19 1.1 0.96 0.87 0.83 0.82 0.81 0.78 0.79 0.8 0.79 0.97 1.01 0.92 0.87 0.84 0.81 0.81 0.83 0.83 0.85 0.88 0.89 1.21 1.32 1.33 1.23 1.16 1.12 1.06 1.08 1.09 1.03 1.04 1.05 1.19 1.14 1.05 0.95 0.87 0.86 0.85
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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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