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Data:
4.2 4.8 20.8 0.9 39.6 2.6 -4.2 17.1 0.85 36.1 3 1.6 22.3 0.83 34.4 3.8 5.2 25.1 0.84 33.4 4 9.2 27.7 0.85 34.8 3.5 4.6 24.9 0.83 33.7 4.1 10.6 29.5 0.83 36.3
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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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