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Data:
81.83 82.58 82.6 82.71 82.98 83.11 83.22 83.32 83.39 83.45 83.52 83.59 83.97 84.48 84.8 84.93 85.14 85.22 85.54 85.5 85.61 85.75 85.89 85.94 86.08 86.3 86.97 87.3 87.62 87.59 87.78 87.87 88.17 88.67 88.84 88.9 88.98 89.27 89.69 89.72 89.79 89.82 89.98 90.09 90.31 90.3 90.48 90.52 90.53 91.38 91.87 91.9 92.08 92.14 92.09 92.32 92.67 92.78 92.96 93.12 93.32 94.12 94.34 94.52 94.81 94.95 94.99 95.03 95.16 95.41 95.46 95.62 95.66 95.96 96.18 96.24 97.03 97.11 97.28 97.74 97.83 98.14 98.18 98.21 98.43 98.67 99.51 99.64 99.83 99.84 99.94 100.17 100.56 101.05 101.17 101.21 101.01 101.92 102.33 102.41 102.5 102.69 102.98 103.11 103.36 103.8 104.07 104.15 104.19 104.64 104.98 105.25 105.43 105.59 105.84 105.87 106 106.14 106.24 106.31
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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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