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Data:
-16.47316856 2.02193837 3.422623336 2.374754596 -3.246846071 7.87118502 2.168133158 5.156669084 9.26691851 0.817208566 -2.807790436 14.27780646 -11.7714986 -3.144019871 -2.602321246 -6.208136909 -8.59062752 0.85194327 -5.463666504 2.707531276 1.746466101 -0.344253512 5.726710626 12.44404877 -17.39586706 -7.628468508 0.247505518 -2.257391538 -1.478762554 13.29076925 -0.120523579 3.319972367 6.811961049 7.772391689 4.833219234 19.40147798 -13.03855467 -10.365971 5.807009572 -5.580724567 -1.191378875 17.40096426 -11.04126405 1.282353053 7.743297418 -0.04691246 0.364668434 2.158961613 -20.16736088 -8.987400427 -6.534642611 -6.450828509 1.764501182 18.85355881 -2.484574227 2.126484964 1.876194907 -2.407155902 -10.560381 2.481263204
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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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