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Data:
227.86 198.24 194.97 184.88 196.79 205.36 226.72 226.05 202.50 194.79 192.43 219.25 217.47 192.34 196.83 186.07 197.31 215.02 242.67 225.17 206.69 197.75 196.43 213.55 222.75 194.03 201.85 189.50 206.07 225.59 247.91 247.64 213.01 203.01 200.26 220.50 237.90 216.94 214.01 196.00 208.37 232.75 257.46 267.69 220.18 210.61 209.59 232.75 232.75 219.82 226.74 208.04 220.12 235.69 257.05 258.69 227.15 219.91 219.30 259.04 237.29 212.88 226.03 211.07 222.91 249.18 266.38 268.53 238.02 224.69 213.75 237.43 248.46 210.82 221.40 209.00 234.37 248.43 271.98 268.11 233.88 223.43 221.38 233.76 243.97 217.76 224.66 210.84 220.35 236.84 266.15 255.20 234.76 221.29 221.26 244.13 245.78 224.62 234.80 211.37 222.39 249.63 282.29 279.13 236.60 223.62 225.86 246.41 261.70 225.01 231.54 214.82 227.70 263.86 278.15 274.64 237.66 227.97 224.75 242.91 253.08 228.13 233.68 217.38 236.38 256.08 292.83 304.71 245.57 234.41 234.12 258.17 268.66 245.31 247.47 226.25 251.67 268.79 288.94 290.16 250.69 240.80
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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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