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Data:
162.32 162.76 163.39 162.58 162.66 162.66 162.66 162.89 163.03 162.38 162.44 162.51 162.51 162.42 162.07 161.45 162.22 162.21 162.21 162.21 162.41 163.96 163.79 163.86 163.86 164.39 164.74 164.27 165.2 165.42 165.42 165.5 165.71 165.74 165.29 164.88 164.88 164.57 164.53 165.03 165.92 165.92 165.92 165.92 166.12 166.34 165.48 165.61 165.61 165.94 165.88 166.23 166.32 166.43 166.43 166.2 166.21 168.02 168.68 168.65
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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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