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Data:
1.94 1.82 1.8 1.79 1.79 1.78 1.81 1.84 1.87 1.87 1.87 1.84 1.82 1.83 1.83 1.82 1.83 1.87 1.88 1.9 1.98 2.03 2.14 2.42 2.73 2.84 2.85 2.94 3.06 3.24 3.18 3.01 2.87 2.73 2.63 2.39 2.26 2.11 2.01 1.99 1.96 1.93 1.98 2.07 2.24 2.31 2.23 2.26 2.28 2.3 2.33 2.26 2.24 2.47 2.55 2.89 3.21 3.21 2.92 2.68 2.4 2.28 2.24 2.2 2.18 2.23 2.24 2.25 2.23 2.25 2.23 2.21 2.17 2.17 2.13 2.12 2.13 2.17 2.33 2.5 2.57 2.59 2.58 2.31
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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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