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Data:
2.08 2.09 2.36 2.99 2.75 1.58 1.69 1.3 1.97 1.84 1.96 1.86 2.75 2.62 2.41 3.61 2.03 1.45 1.4 1.3 1.58 2.1 2.27 2.54 2.55 2.05 2.32 2.6 2.1 1.61 1.55 1.12 1.39 2.18 1.94 2.27 2.41 2.2 2.58 2.9 2.12 1.34 1.07 0.86 1 1.54 1.29 1.44 2.6 2.77 3.31 3.2 2.07 1.42 1.43 1.28 1.59 1.68 2.01 2.52 2.74 3.06 2.69 2.32 1.67 1.04 0.98 0.86 0.97 1.3 1.82 1.99
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R Code
par3 <- '0.1' par2 <- '0.9' par1 <- '0.1' 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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