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Data:
79.58 80.08 80.41 80.34 80.32 80.39 81.01 81.54 82.48 84.68 88.26 90.6 92.46 93.31 93.58 93.92 93.92 93.67 93.76 93.95 93.89 94.07 93.93 93.35 93.58 93.55 93.44 93.38 93.17 92.95 93.37 94.13 94.07 94 94.47 94.81 94.18 94.14 93.96 93.23 93.13 92.51 92.49 92.73 92.75 92.83 92.85 93.27 93.98 94.34 94.57 94.62 94.82 95.07 95.72 96.06 96.54 96.38 96.8 97.02 97.29 97.45 97.95 97.69 97.63 97.35 97.38 98.06 98.34 98.53 98.79 98.77 99.2 99.76 99.84 99.83 99.88 99.48 99.66 99.58 99.89 100.7 101.19 100.99 101.52 101.75 101.56 102.57 102.66 102.62 102.76 102.73 102.26 101.72 101.48 100.93
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R Code
par3 <- '0.10' par2 <- '0.90' par1 <- '0.10' 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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