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Data:
31.5 31.29 31.3 31.06 31.09 31.11 31.13 31.1 31.03 30.74 30.83 30.82 30.8 30.74 30.71 30.58 30.71 30.7 30.7 30.72 30.68 30.78 30.84 30.8 30.8 30.88 30.87 30.92 30.82 30.75 30.75 30.75 30.63 30.52 30.58 30.6 30.6 30.63 30.56 30.61 30.53 30.6 30.6 30.63 30.66 30.34 30.32 30.3 30.3 30.08 29.96 29.91 29.83 29.89 29.85 30.06 29.83 29.95 30.02 30.03 30.03 29.96 29.85 30.12 29.91 29.9 29.92 29.89 29.96 29.72 29.6 29.54 29.54 29.54 29.48 29.55 29.58 29.6 29.6 29.56 29.7 29.76 29.24 29.28
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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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