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Data:
2.79 3.08 3.89 3.7 4.61 5.07 5.22 4.93 5.15 4.8 3.89 3.54 3.34 2.8 1.6 1.53 0.69 -0.11 -0.67 -0.2 -0.62 -0.58 -0.31 -0.25 -0.08 0.13 0.94 1.05 1.59 2.03 2.15 2.06 2.56 2.55 2.53 2.6 2.71 2.82 2.93 2.88 2.89 3.27 3.32 3.14 3.04 3.08 3.39 3.23 3.38 3.41 3.14 2.96 2.73 2.21 2.23 2.56 2.39 2.49 2.17 2.16 1.48 1.09 1.25 1.26 1.39 1.69 1.55 1.19 1.08 0.93 0.98 1.01
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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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