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Data:
0.1605 0.118679012 0.071701299 -0.000333333 -0.016473684 -0.009051282 0.003769231 -0.009051282 -0.013666667 -0.040333333 0.040605634 0.119666667 0.146333333 0.115105263 0.019753247 -0.032194805 -0.04978481 -0.066506173 -0.080658537 -0.10504878 -0.129439024 -0.087759494 0.005876712 0.193289855 0.288151515 0.235686567 0.120826087 0.058714286 0.040605634 0.036888889 0.054690141 0.09184058 0.087285714 0.067117647 0.069875 0.026731343 0.000272727 -0.023875 0.026968254 0.047193548 0.003769231 -0.065235294 -0.109352941 -0.117625 -0.112245902 -0.106310345 -0.095852459 -0.088111111 -0.035219178 -0.024101449 0.068081967 0.066103448 0.031064516 -0.057985915 -0.136090909 -0.189025316 -0.227 -0.254027027 -0.253666667 -0.2145
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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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