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Data:
-3022.358117 283.8527553 639.5234385 404.8679117 -816.3957145 1536.985142 301.3561067 939.3162129 2208.563202 54.73268061 -717.3182617 3397.221024 -2313.992995 -662.7781393 -710.5946877 -1449.779874 -2073.222868 68.07805291 -1279.653945 474.0698683 477.0156032 -204.1820997 1347.465129 3187.979096 -3597.878578 -1564.952319 -20.80556107 -622.0254027 -428.5668792 2882.167534 -129.6005616 667.8258629 1923.825948 1750.155826 1163.933252 5497.497257 -3122.719762 -2291.529237 1415.953813 -1460.889131 -330.3421306 4026.288113 -2811.820376 359.3441917 2194.798182 150.1859051 124.7716748 937.3097979 -5269.112051 -2077.598935 -1722.101796 -1698.161999 266.4052833 3984.259444 -598.6172362 301.2569339 286.9584058 -614.1958414 -2092.37047 449.55762
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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
R Server
Big Analytics Cloud Computing Center
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