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Data:
2.32 1.93 0.62 0.6 -0.37 -1.1 -1.68 -0.77 -1.2 -0.97 -0.12 0.26 0.62 0.7 1.65 1.79 2.28 2.46 2.57 2.32 2.91 3.01 2.87 3.11 3.22 3.38 3.52 3.41 3.35 3.68 3.75 3.6 3.56 3.57 3.85 3.48 3.65 3.66 3.36 3.19 2.81 2.25 2.32 2.85 2.75 2.78 2.26 2.23 1.46 1.19 1.11 1 1.18 1.59 1.51 1.01 0.9 0.63 0.81 0.97 1.14 0.97 0.89 0.62 0.36 0.27 0.34 0.02 -0.12 0.09 -0.11 -0.38 -0.65 -0.4 -0.4 0.29 0.56 0.63 0.46 0.91 1.06 1.28 1.52 1.5
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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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