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Data:
-0.05931 -0.04225 0.00067 0.04599 0.01342 0.01191 0.02796 0.01106 -0.01440 -0.05226 -0.08367 -0.05588 -0.05181 -0.07968 -0.10054 -0.09343 -0.07549 -0.08898 -0.08716 -0.06734 -0.00611 -0.02147 -0.01923 0.00460 -0.00222 -0.01125 0.01432 0.04863 0.03668 0.03959 0.04418 0.07245 0.06993 0.06647 0.09739 0.08473 0.10092 0.12675 0.15963 0.13655 0.12474 0.12405 0.17795 0.18032 0.16380 0.16397 0.18411 0.10490 0.03785 -0.05429 -0.15724 -0.15939 -0.19410 -0.20822 -0.21447 -0.17837 -0.11925 -0.05491 -0.05193 -0.03566 -0.03496
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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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