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Data:
1.27 1.23 1.27 1.22 1.29 1.36 1.44 1.62 1.57 1.22 1.14 1.14 1.17 1.16 1.14 1.15 1.16 1.21 1.22 1.22 1.17 0.95 1 1.01 1.01 1 1 1 1.06 1.22 1.24 1.34 1.3 1.05 1 1 1.01 1.02 1.06 1.09 1.09 1.15 1.25 1.37 1.51 1.35 1.32 1.3 1.39 1.4 1.39 1.42 1.44 1.44 1.45 1.39 1.48 1.32 1.29 1.31 1.27 1.38 1.38 1.45 1.5 1.63 1.73 1.84 1.75 1.34 1.36 1.33 1.37 1.39 1.4 1.4 1.43 1.52 1.54 1.85 1.83 1.29 1.2 1.2 1.21 1.21 1.19 1.18 1.17 1.22 1.25 1.3 1.33 1.18 1.18 1.19
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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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