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Data:
-0.0349270413186066 -0.0596001053081093 0.102927485463034 -0.0493605422998952 -0.0744486964901621 0.0172122166243359 -0.00547655137538673 0.0420595639658103 -0.00126898252030444 0.00417814534569686 0.0502324245318664 0.0506330593271085 -0.078701461734425 0.0492049563319333 -0.0261690888058081 -0.00393879381828204 0.07973936826098 0.0319961742697832 0.00091067709659756 -0.019220682787933 -0.107979686333248 -0.0107667247517434 0.0806227637205843 -0.0529491860051703 0.00528114849116934 -0.0214345304008214 -0.0369393145483388 -0.0680735468724003 -0.0129276272272485 -0.0270496644483431 0.0254460905207515 0.0269982152250543 0.0308225338043865 -0.138807729471492 0.0357776400010795 -0.0228794714726368 0.0894287310745218 -0.0073993180101393 0.0123959579161959 0.0122806920509619 0.0763511379220961 0.079124533029784 0.0615362876121939 -0.019030572914577 0.00196369350314640 -0.0458122032417219 -0.0460091449745193 0.0381733992230888
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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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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