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Data:
68733 41381 51310 39036 42157 52574 39168 41325 40645 42303 38167 8980 66356 50335 47212 42247 45793 48248 40074 39602 41283 41900 29812 7236 56184 33958 34532 30277 30850 35492 33544 27829 33663 35690 27356 8033 62798 37581 44753 37546 36830 50683 38487 36522 45544 43575 36921 11393 74787 49019 56601 47637 49806 50499 42092 39062 44382 43635 41082 17244 70170 43949 52333 41032 47758 76116 30917 32996 31951 26775 30268 18214 47957 31901 35559 30408 30083 35043 30475 28309 31394 36313 40357 38918 44368 33298 29366 28282 30943 32699 29764 25524 29807 35112 32192 36214
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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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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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