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Data:
106.8 114.3 105.7 90.1 91.6 97.7 100.8 104.6 95.9 102.7 104 107.9 113.8 113.8 123.1 125.1 137.6 134 140.3 152.1 150.6 167.3 153.2 142 154.4 158.5 180.9 181.3 172.4 192 199.3 215.4 214.3 201.5 190.5 196 215.7 209.4 214.1 237.8 239 237.8 251.5 248.8 215.4 201.2 203.1 214.2 188.9 203 213.3 228.5 228.2 240.9 258.8 248.5 269.2 289.6 323.4 317.2 322.8 340.9 368.2 388.5 441.2 474.3 483.9 417.9 365.9 263 199.4 157.2
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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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