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Data:
-0.0289 0.0025 0.004 -0.0006 0.0155 -0.0031 0.0061 -0.0193 -0.0113 -0.0155 -0.0279 -0.0135 -0.0263 -0.0361 -0.0413 -0.024 -0.0368 -0.0591 -0.0208 -0.0114 -0.0317 -0.0092 -0.0123 -0.027 -0.0058 0.01 0.0163 -0.003 0.013 0.032 0.0518 0.0494 0.0737 0.0822 0.0464 0.1077 0.1466 0.1115 0.1066 0.1134 0.1716 0.143 0.1587 0.1809 0.1876 0.1684 0.0889 0.0246 -0.107 -0.1178 -0.0822 -0.1312 -0.1296 -0.0877 -0.0485 0.0162 0.0364 0.0531 0.0643
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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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