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Data:
2.7 3 -0.3 1.1 1.7 1.6 3 3.3 6.7 5.6 6 4.8 5.9 4.3 3.7 5.6 1.7 3.2 3.6 1.7 0.5 2.1 1.5 2.7 1.4 1.2 2.3 1.6 4.7 3.5 4.4 3.9 3.5 3 1.6 2.2 4.1 4.3 3.5 1.8 0.6 -0.4 -2.5 -1.6 -1.9 -1.6 -0.7 -1.1 0.3 1.3 3.3 2.4 2 3.9 4.2 4.9 5.8 4.8 4.4 5.3 2.1 2 -0.9 0.1 -0.5 -0.1 0.7 -0.4 -1.5 -0.3 1 0.4 0.3 1.8 3 2.2 3.4 3.4 3.1 4.5 4.6 5.7 4.3 4.5
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R Code
par3 <- '0.1' 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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