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Data:
-564.5024598 -563.2868321 -562.6092123 -561.7289219 -561.1287748 -560.5596749 -559.6534424 -559.3645562 -559.116752 -558.4967141 -558.503492 -558.5209538 -557.0677242 -555.4223769 -555.097832 -553.4948419 -552.6864705 -551.9045613 -551.1060444 -550.6091745 -550.3793745 -550.1054427 -549.8546061 -548.844823 -548.5840858 -548.617565 -548.2909357 -548.0708184 -548.0966998 -547.8101955 -547.5950275 -547.5658663 -547.3702787 -547.351529 -547.0982745 -547.1077645 -546.8794054 -546.6257451 -546.3368134 -545.3938705 -544.2206706 -543.9774587 -543.7544865 -543.5103391 -543.3197988 -543.0791292 -543.0649124 -542.8425928 -542.6238584 -542.4033326 -542.1077162 -541.937633 -541.6831711 -541.6820682 -541.4839707 -541.4566051 -540.3987325 -540.1404426 -536.6900434 -535.8951806
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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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