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Data:
0.88 1.03 0.69 0.71 1.11 1.05 1.03 0.65 0.59 0.77 0.9 1.26 0.96 0.83 0.87 0.79 1.12 0.88 0.64 0.64 0.58 0.5 0.99 1.07 0.89 0.89 0.83 0.86 0.9 1.12 0.88 0.88 0.89 0.82 0.88 0.81 0.88 0.76 1.13 0.85 1.45 1.55 0.71 0.81 0.83 0.73 0.9 0.94 1.78 0.88 1.04 0.83 1.41 0.96 1.3 0.83 1.4 0.91 0.87 0.97 1.19 1.23 1.33 1.17 1.09 0.63 0.89 0.63 1.51 0.97 0.84 0.92 0.95 0.73 1.02 0.79 1.27 0.95 0.75 0.52 0.95 0.82 0.76 1.24 0.94 1.04 1.81 0.95 1.39 0.86 1.15 1.51 0.6 0.72 1.1 1.62 1.84 1.73 1.36 1.07 1 1.49 0.9 1.43 1.54 0.81 1.61 1.3 1.4 1.03 0.79 1.11 1.15 1.03 1.59 1.11 1.33 0.93 1.07 1.14 1.12 0.86 0.82 1.02 1.07 1.31 0.98 0.89 0.8 0.8 0.78 0.97
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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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