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Data:
9.733 9.259 9.864 9.215 10.103 9.380 9.896 10.117 9.451 9.700 9.081 9.084 9.743 8.587 9.731 9.563 9.998 9.437 10.038 9.918 9.252 9.737 9.035 9.133 9.487 8.700 9.627 8.947 9.283 8.829 9.947 9.628 9.318 9.605 8.640 9.214 9.567 8.547 9.185 9.470 9.123 9.278 10.170 9.434 9.655 9.429 8.739 9.552 9.687 9.019 9.672 9.206 9.069 9.788 10.312 10.105 9.863 9.656 9.295 9.946 9.701 9.049 10.190 9.706 9.765 9.893 9.994 10.433 10.073 10.112 9.266 9.820 10.097 9.115 10.411 9.678 10.408 10.153 10.368 10.581 10.597 10.680 9.738
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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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