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840 880 930 920 940 880 980 860 900 930 870 1000 870 860 930 980 1010 860 1140 880 800 900 900 1000 890 890 870 1000 1050 790 1160 830 730 950 980 910 840 860 880 1030 1060 770 1140 890 740 860 1050 840 810 830 920 1070 1040 740 1250 850 790 810 1080 760 840 820 900 1010 1080 780 1150 820 790 820 1130 800 890 810 950 1090 1090 850 1200 790 800 850 1230 800 930 700 1030 1040 1000 830 1190 720 810 870 1190 800 970 690 1010 1030 950 830 1150 750 840 880 1210 830
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R Code
par3 <- '0.1' par2 <- '0.99' par1 <- '0.01' 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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