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Data:
20709.9 21227.3 23009.8 20416.2 20929.6 20763.9 19607.4 19419 19584.9 21878 21745.5 19206.8 21041.3 20407.1 22437 21050.3 20415.7 20220.6 20217.8 18286.4 20781.3 21619.6 20417.6 19988.6 21026.9 20128.3 21671.5 21053.2 19978.6 20572.6 20220.4 19107.6 21989.5 21701.2 19758.3 19843.9 18906.2 19071.2 22385.6 20208.5 19261.4 21470.1 19539.9 17665.1 19917.2 20399.5 19263 19026 18375.4 20165 21138.7 21414.3 20799.2 22773.6 19747.2 19910.7 22051.7 21705 22328.8 20910.3
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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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