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Data:
77 70 67 76 85 106 108 120 108 111 109 104 104 117 111 110 116 118 115 111 112 97 106 93 95 97 81 71 75 70 72 80 78 80 81 99 87 100 95 128 112 104 102 108 103 99 96 85 78 74 106 100 109 87 107 106 109 83 84 83 65 68 61 75 66 78 68 68 174 64 48 45


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highest quantile


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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')

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	46.8582415765041	5.10556881755942
0.02	50.2275339501491	7.30691907185915
0.03	54.1899855753017	7.67951098701696
0.04	57.8793421360073	6.53768410563945
0.05	60.8408082332005	4.92843384894732
0.06	63.0107907968038	3.5660349913642
0.07	64.5400299434632	2.6660942980805
0.08	65.6315121885645	2.15916870443918
0.09	66.4554561712322	1.9067370600427
0.1	67.1285191064533	1.80773023559596
0.11	67.7233814360883	1.81009367937662
0.12	68.2843011038072	1.88680277657425
0.13	68.8386432220817	2.01670460079891
0.14	69.403197498077	2.17808284813384
0.15	69.98714478975	2.34927671492783
0.16	70.593595993315	2.51087739481691
0.17	71.2208245303933	2.64747919272093
0.18	71.8635985987753	2.74876381522001
0.19	72.5146171161908	2.80998260280436
0.2	73.1659035409715	2.83181051504706
0.21	73.8100012887702	2.81955135583942
0.22	74.4408610581923	2.7818017608545
0.23	75.0543718841202	2.72883059952674
0.24	75.6485462582759	2.67100342837229
0.25	76.2234165605207	2.6175378854935
0.26	76.7807297505549	2.57574412072626
0.27	77.3235373306519	2.55075728364779
0.28	77.855769860056	2.54567294156663
0.29	78.3818651877565	2.56196747801446
0.3	78.9064935713912	2.60009113892037
0.31	79.4343961671389	2.66012194937678
0.32	79.9703289805069	2.74235552482039
0.33	80.5190836337137	2.84769685393181
0.34	81.0855403211291	2.97773361308538
0.35	81.6746988500622	3.13441339724952
0.36	82.2916331343279	3.31932142268764
0.37	82.9413251174363	3.53265834075684
0.38	83.6283564557922	3.77212976384267
0.39	84.3564682490943	4.03203675124654
0.4	85.1280353651826	4.30285570804868
0.41	85.9435346501896	4.57150588846213
0.42	86.8011068810347	4.82235332672096
0.43	87.6963135530192	5.03883868707358
0.44	88.622168206722	5.2054809495054
0.45	89.5694801108481	5.30992193932617
0.46	90.5274933932752	5.34465263515974
0.47	91.4847487924131	5.30810766598806
0.48	92.4300508065078	5.20492366472802
0.49	93.3534005515295	5.04530856130825
0.5	94.2467593476299	4.84362883450747
0.51	95.1045386738627	4.61645489878576
0.52	95.9237613951407	4.38038619711831
0.53	96.7038959642435	4.14999970364146
0.54	97.4464177138932	3.93623537892435
0.55	98.154189577589	3.74545854666131
0.56	98.8307729297473	3.57932319232045
0.57	99.4797768071574	3.43540527445316
0.58	100.104333818866	3.30841232462335
0.59	100.706759543939	3.19166479210055
0.6	101.288416142947	3.07853161119846
0.61	101.849766778572	2.96357797929569
0.62	102.390580277764	2.84329576128711
0.63	102.910228341891	2.71638879326406
0.64	103.408011616438	2.58365798214838
0.65	103.883455464787	2.44757607622648
0.66	104.336529475038	2.31166501196048
0.67	104.767763845864	2.17979399805532
0.68	105.1782576301	2.0555092463248
0.69	105.569594878907	1.94149410587533
0.7	105.943701475132	1.83924554461496
0.71	106.30268459143	1.7490317679
0.72	106.648695878179	1.67014848444906
0.73	106.983848139132	1.60141021372124
0.74	107.310195671475	1.54172203677222
0.75	107.629766219271	1.49052513860788
0.76	107.944615844779	1.44793629200344
0.77	108.256875575189	1.41451458633514
0.78	108.568775710643	1.39076550440794
0.79	108.882667902841	1.37667930227233
0.8	109.201103795879	1.37170024358357
0.81	109.527049710853	1.37542398909348
0.82	109.864293760059	1.38898858467684
0.83	110.218018238412	1.41664103939057
0.84	110.595374828527	1.46644397080796
0.85	111.005760831103	1.54875803493285
0.86	111.460440123034	1.67167407096221
0.87	111.971293722679	1.83467495916026
0.88	112.548912998868	2.02423127807439
0.89	113.2009892041	2.2150846385261
0.9	113.932967862046	2.37894893586734
0.91	114.754277810964	2.50103104676722
0.92	115.695703282477	2.60558995734832
0.93	116.848405790252	2.79632713373894
0.94	118.444645202528	3.32329886029376
0.95	121.006576504886	4.67683978966766
0.96	125.543853299996	7.69820551325838
0.97	133.561956373103	13.6095599747009
0.98	146.202982873795	23.3736484483753
0.99	161.856919368626	35.7212461926398