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Data:
-0.182516799296172 -0.94944747492426 0.325776406812306 1.34843784634604 1.75851178494723 -4.42943737703812 -2.31767034001953 -2.79684843911972 1.12860275120424 0.217683629453875 -0.216346021448786 0.255354934382147 2.08016887397565 1.98907623974419 -3.52512220833211 1.92157710024745 -1.23357233233317 -0.578487095948195 5.06860933422247 -4.07661330236988 -1.08022426396436 -2.92628938204488 1.85793956152257 -0.724378886250608 -1.18764122154349 -4.95476521135668 -2.32628727835623 -0.861616376891362 0.240169843746047 -1.29423362584277 -0.405011745027942 0.234630784545567 2.02245409411938 -1.53833721759871 -1.22520941203817 -1.34782503211567 -1.09231372313534 -2.23500733525864 2.01390498049689 -0.25916025754455 -0.251975811363012 3.19306194411413 -0.520346345270884 0.263552410490847 3.6273589881661 0.757824778633043 -2.20481542891670 -0.350907792837528
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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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