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Data:
0.79 2.21 2.12 0.93 5.38 3.14 2.23 11.88 9.31 6.06 2.31 6.84 7.49 0.72 4.48 5.09 7.44 1.41 5.77 4.84 2.96 3.12 3.83 3.11 2.86 4.06 3.32 1.21 0.8 2.52 1.21 1.17 8.17 5.65 1.24 1.46 4.36 3.38 1.87 1.03 1.29 0.82 2.84 1.27 3.92 1.95 4.21 5.19 5.51 2.19 2.57 1.53 2.17 2.15 2.07 3.97 0.42 6.86 1.02 2.9 5.87 5.14 2.34 4.73 2.02 1.03 1.58 5.3 1.97 4.38 2.98 3.23 1.89 1.41 1.53 3.07 0.61 1.68 2.92 1.16 1.58 2.79 1.88 5.57 6.22 4.61 1.89 5.02 2.1 5.55 1.03 1.17 5.69 8.13 1.91 1.22 6.29 3.84 1.66 1.21 3.69 5.83 15.82 3.26 0.99 0.81 3.71 1.53 2.08 2.54 3.46 2.89 1.78 6.08 3.78 7.78 1.68 0.87 1.43 2.48 2.94 0.98 5.28 3.58 5.6 1.39 1.56 1.16 4.98 7.52 0.79 2.79 1.91 4.16 2.28 1.1 4.44 3.88 10.8 3.65 2.71 5.69 0.87 4.94 2.45 3.11 2.77 1.49 5.61 1.21 2.7 1.24 7.97 4.06 5.81 1.29 1.24 3.31 3.67 1.32 4.25 2.01 7.25 5.79 1.51 0.91 1.32 2.66 0.48 1.13 2.7 7.92 2.34 3.33 5.47 1.24 2.84 4.94 7.93 8.22 2.91 2.32 3.57 1.65 2.07 1.03 0.99 1.37
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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,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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Big Analytics Cloud Computing Center
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