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Data:
1.7319479184152E-14 1.7319479184152E-14 1.7319479184152E-14 1.7319479184152E-14 0.0060180723255177 -0.0060180723255461 0.0060180723255177 -4.5741188614556E-14 -4.5741188614556E-14 -4.5741188614556E-14 -4.5741188614556E-14 -0.0050125418235458 -0.0090863825560015 -4.3964831775156E-14 0.0090863825559562 -1.3322676295502E-15 -1.3322676295502E-15 -1.3322676295502E-15 -1.3322676295502E-15 0.0030105391528985 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 -0.010070578563573 0.010070578563623 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 2.3536728122053E-14 0.0020222453807235 -4.4408920985006E-14 -0.0020222453807444 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 0.0020222453807235 -4.4408920985006E-14 0.0080483331828556 2.7089441800854E-14 -0.010070578563573 0.010070578563623 -0.010070578563573 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 -0.093287934423576 0.085157808340281 -2.6201263381154E-14 -2.6201263381154E-14 0.0081301260832736 0.010070578563623 2.7089441800854E-14 -0.010070578563573 0.010070578563623 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 2.7089441800854E-14 -0.010070578563573 0.010070578563623 2.7089441800854E-14 -0.010070578563573 0.010070578563623 2.7089441800854E-14 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 -0.0080483331828729 -4.4408920985006E-14 -4.4408920985006E-14 -0.0020222453807444 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 0.0090680722139234 -4.7073456244107E-14 -4.7073456244107E-14 -0.0090680722139469 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 0.0090680722139234 -4.7073456244107E-14 -0.0090680722139469 2.3536728122053E-14 2.3536728122053E-14 -0.0020263431452765 -4.3964831775156E-14 -4.3964831775156E-14 -4.3964831775156E-14 -4.3964831775156E-14 -4.3964831775156E-14 -4.3964831775156E-14 -4.3964831775156E-14 0.0020263431452561 2.3536728122053E-14 2.3536728122053E-14 0.0090680722139234 0.001002506349653 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 0.010070578563623 -0.010070578563573 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 -0.010070578563573 0.010070578563623 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 -0.010070578563573 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 2.3536728122053E-14 0.010070578563623 -0.010070578563573 2.3536728122053E-14 2.3536728122053E-14 0.010070578563623 -0.010070578563573 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 2.7089441800854E-14 -0.010070578563573 0.010070578563623 -0.010070578563573 2.3536728122053E-14 0.010070578563623 2.7089441800854E-14 2.7089441800854E-14 -0.010070578563573 -0.0010126583143766 9.7699626167014E-15 9.7699626167014E-15 9.7699626167014E-15 9.7699626167014E-15 9.7699626167014E-15 -0.0081383969029902 -1.9095836023553E-14 -1.9095836023553E-14 -1.9095836023553E-14 -1.9095836023553E-14 -1.9095836023553E-14 -1.9095836023553E-14 -1.9095836023553E-14 0.0081383969029809 9.7699626167014E-15 -0.0081383969029902 -1.9095836023553E-14 -0.0092355710331189 -3.6859404417555E-14 -3.6859404417555E-14 0.017373967936063 9.7699626167014E-15 9.7699626167014E-15 9.7699626167014E-15 -0.0081383969029902 -1.9095836023553E-14 0.0081383969029809 -0.0081383969029902 -1.9095836023553E-14 0.0081383969029809 9.7699626167014E-15 -0.0081383969029902 -1.9095836023553E-14 0.0081383969029809 9.7699626167014E-15 -0.0081383969029902 -1.9095836023553E-14 -1.9095836023553E-14 -1.9095836023553E-14 0.0061099986415809 2.2204460492503E-15 2.2204460492503E-15 -0.0010157441197975 3.8191672047105E-14 -0.0081633106391621 0.008163310639199 3.8191672047105E-14 0.60391604683204 -0.61207935747116 0.008163310639199 3.8191672047105E-14 3.8191672047105E-14 3.8191672047105E-14 -0.0081633106391621 -1.3322676295502E-15 -1.3322676295502E-15 0.008163310639199 3.8191672047105E-14 3.8191672047105E-14 -0.0081633106391621 -1.3322676295502E-15 -1.3322676295502E-15 -1.3322676295502E-15 -1.3322676295502E-15 -1.3322676295502E-15 -1.3322676295502E-15 0.008163310639199 3.8191672047105E-14 3.8191672047105E-14 3.8191672047105E-14 3.8191672047105E-14 -0.0081633106391621
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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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Raw Output
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R Server
Big Analytics Cloud Computing Center
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