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Data:
100.4 97.7 97 96.5 98.4 106.3 103.1 102.4 95 98.1 106.1 99.1 101.2 95.5 99.8 97.1 97.5 96.8 97.7 100.9 94.3 99.5 100.8 97 99.2 101 102.3 97 91.2 97.6 95.7 100.5 94.4 102.9 105.1 98.8 100.7 99.6 107.7 102.9 101.6 102.7 110.5 109.8 94.3 102.5 105 102.3 107.7 100.3 99.5 95 97.7 96.3 97.8 106.4 96.1 106.2 114.7 111.9 121 117.7 115.4 114.3 109.5 108.1 108.2 99.1 101.2 98.1 95.5 97.9 98.2 98.7 95.6 95.8 94.4 96.5 103.3 104.3 104.5 102.3 103.8 103.1 102.2 106.3 102.1 94 102.6 102.6 106.7 107.9 109.3 105.9 109.1 108.5 111.7 109.8 109.1 108.5 108.5 106.2 117.1 109.8 115.2 115.9 119.2 121 118.6 117.6 114.6 110.6 102.5 101.6 107.4 105.8 102.8 104 100.4 100.6
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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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