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Data:
83.5 83.6 83.9 83.9 84.2 84.4 84.6 84.8 84.8 84.9 85 85.1 85.3 85.5 86.1 86.2 86.3 86.5 86.5 86.6 86.8 87.3 87.7 87.8 88.1 88.8 89.3 89.2 89.3 89.6 89.6 89.9 90.2 90.2 90.4 90.5 91.5 91.5 91.8 92.2 92.4 92.7 93.1 93.1 93.5 93.9 94.3 94.7 95.3 95.9 96.2 96.7 96.7 96.9 97.3 97.4 97.9 98.4 98.4 98.8 98.9 98.9 99.3 99.4 99.7 99.8 99.7 99.9 100.4 101.1 101.3 101.4 101.8 102.2 102.4 102.5 102.8 103 103.2 103.2 103.6 103.7 103.7 103.8 104.2 104.5 104.5 104.8 105.2 105.3 105.5 105.4 105.7 106.8 106.8 107
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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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