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Data:
88.83 89.01 88.21 87.78 87.93 88.11 88.2 88.12 88.38 87.65 88.24 87.83 87.75 87.88 87.61 88.05 87.77 87.79 88.34 88.48 88.75 87.95 89.09 88.73 89.24 89.77 89.84 90.97 91.53 92.2 92.27 92.42 92.07 91.73 92.1 91.68 92.63 93.02 92.66 93.23 93.79 93.92 94.04 94.23 94.37 94.29 94.38 94 94.11 93.98 93.42 93.3 93.32 93.75 93.82 94.06 94.09 93.64 93.9 93.18 93.54 93.55 93.8 93.39 93.27 93.58 93.47 93.75 93.3 92.65 92.96 92.84 93.29 93.57 93.54 94.38 93.98 94.48 94.63 95.45 95.59 94.76 95.66 95.03 96.45 97.15 97.5 98.54 99.54 100.33 100.28 101.81 101.91 101.92 102.68 101.9 102.14 102.3 102.06 102.4 102.99 102.99 102.83 103.01 102.6 102.18 102.6 101.44
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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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