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Data:
100.71 100.75 100.75 100.70 100.77 100.44 100.17 100.21 100.27 100.29 100.33 100.35 100.94 101.07 101.01 100.86 100.71 99.95 100.02 100.03 100.04 99.73 99.76 99.83 100.08 99.35 99.43 99.53 99.03 99.05 99.07 99.23 99.03 99.06 99.13 99.14 100.91 100.97 100.55 100.68 100.31 100.31 99.28 99.24 99.29 99.27 99.26 99.25 99.57 98.97 99.00 98.88 98.90 98.92 98.80 98.83 98.88 98.88 98.89 98.89 99.05 99.20 99.13 98.92 98.98 98.99 99.08 99.10 99.10 99.06 99.05 99.11 99.75 99.80 99.95 99.69 99.55 99.14 99.05 99.00 99.03 99.16 99.01 99.00 99.90 100.18 100.20 100.13 99.85 99.88 99.88 99.89 99.96 100.05 100.04 100.06 99.72 99.70 99.63 99.73 99.77 99.76 99.61 99.61 99.59 99.42 99.52 99.46
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R Code
par3 <- '0.10' 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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