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Data:
31.1 31.8 32.5 34.4 35.5 35.5 36.6 37.1 37.9 38.1 39 41.5 41.8 41.9 44.6 46.1 46.4 47.2 47.7 49.2 49.3 49.3 49.5 50.1 51.9 52.6 53.2 53.5 53.7 53.7 53.9 54.1 54.8 55.4 55.9 56.8 58.4 59.3 60.3 60.5 60.8 61 61.1 61.3 61.4 61.5 63.9 63.9 64 64.1 64.5 64.5 65.9 66.8 68.7 69.2 69.6 70.2 70.6 70.7 70.7 71 72.1 73.7 77.4 79.7 91.6 93.6 94.3 97.3 101.7 103 103.1 104.6 107.2 107.7 108.3 108.8 113.1 113.8 113.8 116.5 116.9 117.6
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R Code
par3 <- '0.1' par2 <- '0.9' 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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