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Data:
49.1 52.7 55.1 60.4 57.5 55.9 62.6 61.3 67.1 68.6 74.8 76.9 85.7 86.5 90.8 89.7 96.3 107.5 109.2 100.2 116.8 120.1 123.3 130.2 131.4 125.6 124.5 134.3 135.2 151.8 146.4 140.0 127.8 148.0 165.9 165.5 179.9 190.0 189.8 190.9 203.6 183.5 169.3 144.2 141.5 154.3 169.5 194.0 203.2 192.9 209.4 227.2 263.7 297.8 337.1 361.3 355.2 312.6 309.9 323.7 324.1 355.3 383.4 395.1 412.8 407.0 438.0 446.1 452.5 447.3 475.9 487.7
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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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