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Data:
95.97 96.22 95.8 96.02 96.04 96.15 96.15 95.99 96.08 96.29 96.3 96.44 96.44 96.83 96.7 97.06 97.64 97.61 97.61 97.61 97.55 97.58 97.79 97.79 97.79 97.79 98 98.37 98.68 98.89 98.89 98.89 98.88 98.97 99.05 99.05 99 99.03 99.2 100.3 100.79 100.75 100.75 100.17 99.98 99.93 100.04 100.04 100.49 100.71 100.7 101.27 101.07 101.17 100.71 100.59 100.52 100.65 100.62 100.62 100.59 100.42 100.55 100.41 100.4 99.93 100.26 100.34 100.24 99.98 100.08 100.24
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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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