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Data:
100.3 101.9 102.1 103.2 103.7 106.2 107.7 109.9 111.7 114.9 116.0 118.3 120.4 126.0 128.1 130.1 130.8 133.6 134.2 135.5 136.2 139.1 139.0 139.6 138.7 140.9 141.3 141.8 142.0 144.5 144.6 145.5 146.8 149.5 149.9 150.1 150.9 152.8 153.1 154.0 154.9 156.9 158.4 159.7 160.2 163.2 163.7 164.4 163.7 165.5 165.6 166.8 167.5 170.6 170.9 172.0 171.8 173.9 174.0 173.8 173.9 176.0 176.6 178.2 179.2 181.3 181.8 182.9 183.8 186.3 187.4 189.2 189.7 191.9 192.6 193.7 194.2 197.6 199.3 201.4 203.0 206.3 207.1 209.8 211.1 215.3 217.4 215.5 210.9 212.6
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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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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