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Data:
2.07 2.08 2.08 2.08 2.09 2.09 2.09 2.1 2.1 2.1 2.11 2.11 2.11 2.13 2.18 2.2 2.21 2.21 2.22 2.22 2.23 2.23 2.23 2.23 2.24 2.25 2.26 2.27 2.28 2.29 2.3 2.3 2.3 2.32 2.32 2.32 2.33 2.34 2.34 2.34 2.35 2.35 2.36 2.37 2.37 2.37 2.38 2.38 2.38 2.39 2.4 2.41 2.42 2.43 2.43 2.43 2.43 2.44 2.44 2.45 2.45 2.48 2.49 2.49 2.5 2.51 2.52 2.53 2.54 2.54 2.56 2.56
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R Code
par3 <- '0.01' 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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Big Analytics Cloud Computing Center
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