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Data:
22943 21413 20631 19775 17506 20688 32631 34062 29159 25871 23719 25638 27596 28006 27662 26655 25213 28434 40388 42758 37956 33490 31578 34766 32324 32046 29565 28284 26366 27530 39728 41528 36458 32301 28985 29118 29249 28036 26326 24942 23280 23969 35948 37639 34327 30133 27549 27990 30437 30464 28471 26882 25806 26465 36416 42870 40489 36645 33841 33496 34504 34699 33322 32160 30173 30782 43062 46223 45191 40671 37251 36870
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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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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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