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Data:
170.47 122.04 145.60 138.95 144.90 162.50 107.52 129.35 161.84 152.35 132.43 110.96 129.46 137.26 116.56 115.63 107.86 104.77 145.32 139.09 117.68 116.75 117.75 152.59 129.69 121.32 135.32 141.33 148.91 180.11 199.00 169.50 164.71 206.76 196.00 200.22 206.39 289.46 287.85 288.38 308.17 265.71 173.05 131.45 121.58 109.11 106.56 88.07 95.83 78.45 67.43 66.17 73.04 72.20 84.21 126.16 146.33 190.57 209.16 674.50
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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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