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Data:
-0.356755792301585 -1.6291666948379 0.460185550737049 0.42730865329935 0.0489441775557294 0.357682794541296 -0.0659454002544119 -0.0458584149762463 0.311920964930959 -1.01523582878399 1.22702468909963 -0.43681709919404 -0.784301177447286 -0.515881130828691 1.45172379235195 -0.759894689037895 2.06643220654799 -1.22367184419175 -1.55985216630802 0.132555338441181 0.203984874213615 0.460179327140889 0.481106043156997 0.0258094793556829 0.666139163148585 0.317002046653185 -0.427736799488161 1.06554833990888 0.182317555590142 -0.470323444471103 1.05745411073187 0.9188967536934 0.307897679374394 -1.00327142999205 -1.54574711035025 -0.576669265418929 1.87974760816238 -0.724383519132804 0.470278823150111 -0.390178888685926 -0.85462054067199 -1.47072859017166 0.0518668604395884 -0.357611864795985 0.612099066974793 0.442746939994066 0.307768821334733 -2.80509741853685 0.911905304665993
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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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