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Data:
62239.3 64816.6 62625.3 67923 64363.7 67342 64411.2 69174.5 66290.2 69336.8 66712.2 72225.9 68229.5 71096.3 68407.9 74522.4 71798.4 75074.3 72694.6 78789.4 74814.5 78303.2 75431.6 82600.7 78830.5 82168.1 79493.2 86876.6 83478.5 87003.2 83672.7 90914.2 86448 90577.7 86621.1 91418.5 84275.4 87677.9 85149.6 92600 87111.3 92293.9 89060 97281.6 91812 95980.4 92043.7 100079.2 94384.8 97900.5 93630.8 102255.2 95251.8 100001.8 95689.8 104298 97435.1 101220.2 97537 105834.9
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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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