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Data:
27.00 26.88 27.38 26.82 27.00 26.15 25.85 26.17 25.66 25.72 25.42 25.10 26.20 26.39 26.27 26.63 21.10 20.30 20.61 21.05 20.45 20.91 21.22 20.85 21.90 22.71 22.40 22.81 23.96 23.37 23.55 23.01 22.63 22.63 22.00 22.15 22.00 22.00 21.84 22.10 22.37 21.83 21.77 21.89 20.76 20.21 20.19 20.01 19.16 18.50 17.41 18.14 18.60 18.32 18.40 18.16 17.29 16.65 16.36 16.32 17.37 17.30 18.10 19.00 18.38 18.41 18.10 17.87 18.70 18.81 18.88 19.44 18.60 18.80 18.62 18.24 17.84 17.85 17.67 17.99 18.15 18.39 18.07 18.39
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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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