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Data:
82.6 85.99 86.85 86.12 97.19 89.8 90.27 90.68 90.05 90.28 91.52 88.3 85.31 87.86 87.77 88.44 88.73 94.4 94.09 90.32 89.68 94.15 95.2 91.82 90.33 95.14 96.06 97.21 100.33 98.79 102.48 99.29 98.83 97.25 94.55 93.53 93.58 95.79 94.77 94.2 96.23 92.3 88.86 86.44 86.21 88.57 90.69 89 86.88 90.65 90.68 89.64 102.62 101.84 92.51 94.29 94.68 96.94 94.03 89.65 84.9 89.07 89.8 93.22 92.23 98.41 96.63 89.8 90 92.13 93.27 90.81 85.42 88.28 88.73 90.18 92.74 96.13 94.85 94.25 96.94 101.22 98.71 95.51 93.91 98.17 97.59 99.64 107.88 108.49 100.25 99.27 101.73 101.25 97.09 94.74 94.53 93.48 96.05 106.22 98.33 99.86 93.78 88.96 83.77 89.46 86.78 88.4 87.19 92.23 95.99 104.75 105.63 108.71 96.4 93.31 93.77 98.7 95.04 95.61
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R Code
par3 <- '0.1' par2 <- '1' 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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