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Data:
-5.57188623643403e-05 0.000673127001655781 0.00253297316798237 -0.00312808800265659 6.06736685254191e-05 0.00111459533092098 -0.000554109520648384 -0.00105302564390300 0.00104708036627266 -0.000154081652574897 0.00384608131631652 -0.00119915735301702 -0.000654000489824518 0.00147251443605623 -0.000700006059835063 -0.00061908177055739 0.000837030387252926 0.00112904739358168 -0.000635971834993874 0.000438787250423991 0.00336388391216243 0.000921403408594523 -0.000666757721707773 -0.00102031957840900 -0.000796646941257639 -0.00332057539851693 -0.000182532249361493 0.000146444976543607 0.000563712163999504 -0.00101555676532265 -0.000213138748455123 -0.00116972320289465 0.000718163786614911 0.00147451936379633 -0.00186871515930147 -0.00152438264067532 -0.00079919301702642 0.00214361864863578 0.00246081566765619 -0.00105955030987362 -0.000841465941827341 -0.000224431304780554 -0.000524348696489676 0.00168130096323857 -0.00179203973258881 8.57375031507516e-05 -0.000771092454595768 -0.000903583373710958 0.000148807028873512 -0.001557405462672 0.000344209067865560 -0.00101577409715098 0.000968280070164763 -0.000691907060623672 -0.000647161091857317 0.000306078767940221 -0.00143204637452955 0.00171652552326860 0.00100568755956631 -0.00162283353151299 -5.03611946386278e-05 -0.00139199227766638 0.0008205486056255 0.00106165242946242 -0.00149168951466355 0.000113318551053342 -0.000798705188071938 0.000725657525939686 0.000996463288562474 0.000551870084508547 -0.000750413138897793 -0.00107155858159102 0.000778446826870656 -0.000420986168065270 -0.00123476222127950 5.58572848751406e-05 0.000674648736605934 -0.00070571283485043 0.000562433086011177 0.00155795278362076 0.000246475697694884 -0.000138379316298359 -0.000372926968554567 0.00161826258007914 -0.00118416871764147 -1.79064625009521e-05 -0.000530448371326978 0.000513060612174883 -0.000488611530751738 -0.000344435665802584 0.000842398928486991 -0.00078884664263527 -0.00030481479842588 -0.00072415539117241 0.000502998571283987 -0.000437715789622652 -0.000201547985612967 -0.000674925273024028 -0.000139783804754848 -0.000849121145158096 6.60224785191873e-05 0.000113764899993581 0.00159428581141906 0.00113767761833825 0.00355745661277584 0.00266114068025193 0.00242685751739785 -0.00123747069021010 0.000630850445637065 -0.000959554038128756 -0.000666732374209195 -0.00142693285098644 -0.00158022058363810 0.00143352595627639 -0.00138297408790195 0.00105401647418059
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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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R Server
Big Analytics Cloud Computing Center
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