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Data:
121.67 121.65 121.61 121.5 121.41 121.41 121.4 121.38 121.34 121.19 120.96 120.96 120.96 120.9 120.86 120.73 120.53 120.53 120.53 120.52 120.51 120.43 120.29 120.27 120.27 120.24 120.21 120.06 119.86 119.85 119.85 119.83 119.71 119.57 119.2 119.13 119.13 119.09 118.9 118.54 118.12 118.11 118.1 118.08 117.91 117.63 117.28 117.2 117.17 117.14 116.96 116.34 115.99 115.99 115.97 115.92 115.63 115.31 115.13 115.09 115.07 115.01 114.64 113.86 113.34 113.33 113.32 113.26 113.2 112.61 112.28 112.16


Sample Range: (leave blank to include all observations)
From:
To:

lowest quantile


highest quantile


step size


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Title:
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Label x-axis:

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')

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

Harrell-Davis Quantiles
quantiles	value	standard error
0.01	112.231660923552	0.196740876371237
0.02	112.3711353169	0.317466645975273
0.03	112.55410848096	0.3990935831678
0.04	112.750362567473	0.415717977398983
0.05	112.936967601483	0.389484024329245
0.06	113.104265777365	0.362062983461705
0.07	113.255157050596	0.369864201996029
0.08	113.399853158695	0.423387956836312
0.09	113.549578159002	0.506781905429477
0.1	113.711930556019	0.596001865684595
0.11	113.888944832738	0.670350720716094
0.12	114.077551411146	0.716519027393349
0.13	114.271492070757	0.730034149578366
0.14	114.463657457122	0.714604918181595
0.15	114.648044637001	0.679610853850036
0.16	114.820902175901	0.636679122942111
0.17	114.980998758782	0.596414174316712
0.18	115.129219593688	0.566081980994627
0.19	115.26781562078	0.548743751619019
0.2	115.399613843279	0.543917353673216
0.21	115.527393872034	0.549171761536163
0.22	115.65350920039	0.561648669189412
0.23	115.779731251244	0.578865699041271
0.24	115.907242785206	0.598824035506288
0.25	116.03670243496	0.619786242856371
0.26	116.168326178525	0.640066315831253
0.27	116.301963281845	0.658002901374556
0.28	116.4371678905	0.6721167670593
0.29	116.573276554643	0.681350413425921
0.3	116.709498425361	0.685265701329728
0.31	116.845015241021	0.684112789407623
0.32	116.979079545681	0.678745680233169
0.33	117.111096261008	0.670417513404593
0.34	117.240675521267	0.660524801972651
0.35	117.367651428415	0.650375816503465
0.36	117.492068782727	0.641035241605968
0.37	117.61414516238	0.633256889646948
0.38	117.734217814049	0.627479045078813
0.39	117.852684147124	0.62384194692062
0.4	117.96994260033	0.622199337373856
0.41	118.086338684452	0.62212370905474
0.42	118.202119844259	0.622927071506628
0.43	118.317402329986	0.623721095471303
0.44	118.432152880639	0.623523069522804
0.45	118.546187030556	0.621390445883562
0.46	118.659184008524	0.616551539006434
0.47	118.770715828819	0.608499938714531
0.48	118.88028599636	0.5970329701536
0.49	118.987372007092	0.582232871157077
0.5	119.091465920844	0.564405861719717
0.51	119.192108598848	0.544003621043319
0.52	119.288915174657	0.521551452307419
0.53	119.381591245866	0.497598577219638
0.54	119.469940576907	0.472692774942361
0.55	119.553865607986	0.447369928774201
0.56	119.633361979925	0.422144040783481
0.57	119.708508035197	0.397486695024679
0.58	119.779450231028	0.373794556623961
0.59	119.846385747895	0.351354215751259
0.6	119.909544144981	0.330319859222807
0.61	119.969170363151	0.310717149150484
0.62	120.025511382757	0.292476708993121
0.63	120.078808287167	0.275487832223446
0.64	120.129294510159	0.259654628774214
0.65	120.177199980118	0.244937481416171
0.66	120.22276002682	0.231371482414291
0.67	120.266227403847	0.219064916214388
0.68	120.307885468815	0.208188242015639
0.69	120.348060192227	0.198963047935042
0.7	120.387128086257	0.191650918348531
0.71	120.42551655422	0.186529089178033
0.72	120.46369315519	0.183833273315992
0.73	120.50214162403	0.183659808603847
0.74	120.54132565526	0.185851817300876
0.75	120.581646100122	0.189927633466645
0.76	120.623401888206	0.195110668806794
0.77	120.666767345497	0.200477766915104
0.78	120.711796290644	0.205187212668035
0.79	120.75845524749	0.208710742027284
0.8	120.806675662067	0.210981557858293
0.81	120.856402418736	0.212376024130869
0.82	120.907609520192	0.213478340078744
0.83	120.960259524234	0.214658861617919
0.84	121.014203625925	0.215628429837937
0.85	121.069050129776	0.215229451005456
0.86	121.124059392743	0.211661211718069
0.87	121.178137768849	0.203116627075528
0.88	121.229988008845	0.188597519333847
0.89	121.278424129419	0.168597838027527
0.9	121.322783808465	0.145395093254237
0.91	121.363293712005	0.12282355684343
0.92	121.401195782969	0.105455446600398
0.93	121.438462741358	0.0967634349327983
0.94	121.477051741027	0.0961860349608334
0.95	121.517873281576	0.0980949015566024
0.96	121.55992229196	0.0948082914325672
0.97	121.600137200081	0.0809222842772642
0.98	121.634257575905	0.0571385989925378
0.99	121.65828621665	0.0323047585467433