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Data:
80.44 80.9 81.03 81.6 81.56 82.08 83.44 83.55 82.63 82.43 82.42 82.48 82.51 83.23 83.41 83.88 83.96 84.32 85.82 85.72 84.36 84.36 84.36 85.08 84.95 85.62 86.22 86.4 86.71 87.51 89.22 89.43 88.24 88.9 88.78 89.25 88.8 89.46 89.66 90.29 90.08 90.42 92.14 92.09 91.35 91.22 90.99 91.48 90.98 91.52 91.62 92.12 92.26 92.18 94.12 93.82 93.2 93.34 93.11 93.63 93.29 93.69 94.19 94.82 94.52 94.94 96.87 96.6 95.43 95.56 95.37 96 95.6 96.17 96.26 97.2 97.23 97.74 99.37 99.37 98.22 98.27 97.98 98.53 97.98 98.63 98.74 99.37 99.51 99.66 101.62 101.71 100.49 100.81 100.48 101.01 100.62 101.12 101.45 101.34 101.39 101.93 102.42 102.18 102.72 102.43 102.35 102.69
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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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