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Data:
EstimatedARIMAResiduals Value -0.00396671269256706 0.111314976037103 0.0682740086174928 -0.227111870047336 -0.0913453054264917 0.142031609901945 -0.0148431426417289 0.0159001587559324 0.0387654462009301 -0.231666918382834 0.118284321646778 0.0769722354057693 -0.03861152971703 -0.00555263316920203 -0.157784204284717 -0.017944571417612 -0.0152657456648827 -0.0390854765658281 -0.0914782243150564 0.0580715093834441 -0.0921932301655767 -0.0516908644481382 0.134595157528573 0.0305495311701961 0.0174618681293164 0.0398046301832505 -0.0311816474642415 -0.0969684684902288 -0.184800867379907 0.0597654936100393 -0.0210069897652283 -0.0612718555927389 0.173481988903269 0.137720289923430 0.134527367433644 -0.0193480250967496 0.0949563605309157 -0.000704240402552093 0.161442750558655 -0.0904257098922774 0.177090981495639 0.043706007040313 0.00365367371078285 -0.0829872681780013 0.0937601982702212 -0.0531229737676275 -0.328660767305424 -0.0767819308385851
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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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