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Data:
100.34 115.78 114.6 114.2 115.88 125.22 161.71 165.01 135.78 153.67 125.52 135.29 103.05 120.79 120.17 119.62 121.17 129.86 167.8 167.14 140.55 158.44 131.07 140.55 106.15 123.65 122.8 122.25 123.88 132.96 171.82 173.69 149.5 164.44 133.37 143.77 69.49 84.5 82.3 78.8 79.47 88.93 138.13 139.69 114.43 128.65 95.92 98.22 56.65 69.6 66.91 63.76 64 35.24 45.3 43.02 43.08 43.17 46.38 70.85 72.81 59.51 67.54 56.51 53.82 112.55 127.65 126.51 126.08 127.34
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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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