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Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationThu, 08 Oct 2015 14:16:23 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Oct/08/t14443102248eh2bc6nycbpg6d.htm/, Retrieved Fri, 01 Nov 2024 00:33:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=281453, Retrieved Fri, 01 Nov 2024 00:33:11 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Harrell-Davis Quantiles] [Percentielen moto...] [2015-10-08 13:16:23] [269a3741545986d4bc4555135c508362] [Current]
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Dataseries X:
989
1215
2911
2372
2013
2050
1580
1407
903
709
490
206
1101
1189
2877
2489
2145
1837
1613
1296
849
642
475
224
920
1263
2999
2988
2163
2391
1556
1089
976
626
392
203
1052
1034
2353
3075
2309
2009
1464
1099
1035
792
406
187
862
822
2128
2264
1987
1728
1311
1152
945
704
526
361
1035
869
2698
2367
1926
1843
1404
1314
1007
865
587
339
1143
1807
2380
2337
2117
1789
1569
1305
952
810
473
278
993
1038
2257
2284
1747
1515
1233
882
1029
707
391
239
592
692
2127
1854
1468
1535
1203
880
821
604
315
139
528
654
1895
1598
1519
1242
1027
762
735
485
281
131
651
611
1898
1385
1047
1008
843
833
711
444
315
204
473
566
1611
1301
1154
1158
862
801
559
404
223
158
548
647
1757
1326
1308
1175
992
808
758
553
310
146




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281453&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281453&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281453&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Harrell-Davis Quantiles
quantilesvaluestandard error
0131NA
0.01140.95293512961912.8336551828616
0.02159.08685760251822.8211264089535
0.03180.10445600774725.7211792050035
0.04199.74518682953625.4241340775403
0.05217.95993267787429.6788346696233
0.06237.20479466432837.4374100942633
0.07258.7662664874644.4710255131616
0.08282.14803500694549.0490005440849
0.09306.30999088529951.9228646029555
0.1330.59062180821254.2834506070477
0.11354.76613654560756.4253446639288
0.12378.73476876692257.9962324318456
0.13402.31691488032358.6873059622645
0.14425.26911618055658.4991067772105
0.15447.38316465352557.6770917203172
0.16468.55587951683156.5779010625624
0.17488.7982583281355.5164671521427
0.18508.20168449250554.6550984984757
0.19526.89309043380854.028398049342
0.2545.00519041868653.6393116744142
0.21562.66899315106853.5344643747961
0.22580.0176963457653.7761545572391
0.23597.18741706669854.3950746282738
0.24614.30932431876655.3716159270503
0.25631.49713543336856.6297297526944
0.26648.83559827478258.0684551511121
0.27666.37159199688959.5538356005848
0.28684.10611825119260.9224646342083
0.29701.9862463291561.9685855386125
0.3719.90000591821962.4725470332296
0.31737.68072654724862.2317568501044
0.32755.12703366070361.1491090202462
0.33772.03959468379559.2950592078298
0.34788.26790697450556.9383166645049
0.35803.7540983056154.5094082521647
0.36818.55938262187252.5159382831688
0.37832.86313128721351.4077044851596
0.38846.93229010960651.4665891632158
0.39861.06699037820352.7078700625834
0.4875.53451475938254.8562729743364
0.41890.50737805556557.4064804207712
0.42906.02163072211759.7460062716682
0.43921.96791125694261.3048608047424
0.44938.12010376141561.7162949345843
0.45954.19614398848460.8996310502328
0.46969.935741439559.1086519912785
0.47985.17416099199556.8647705442502
0.48999.89194011187754.8347070489273
0.491014.2272691134753.6678686280485
0.51028.44839326453.8219433817037
0.511042.8945280476755.4392707973384
0.521057.902260558458.3192088099402
0.531073.7378349724462.00347093757
0.541090.5529173438465.9354675155808
0.551108.3730967504469.6198127158458
0.561127.1174273357372.7111399942361
0.571146.638186287875.0748087826637
0.581166.766618395276.7380123481258
0.591187.3537135933377.864205320189
0.61208.3020274162578.6756993192204
0.611229.5898707583679.4859852516927
0.621251.2888058420880.6555947722188
0.631273.5697990706482.5737555616552
0.641296.6880344306885.5514706596488
0.651320.9381781281989.6495131075636
0.661346.5837421058994.5984736712832
0.671373.7814943755899.7935103160467
0.681402.53376999254104.537795340311
0.691432.69733645091108.285847755927
0.71464.05431574176110.910062833217
0.711496.41763066661112.758272161617
0.721529.71853874514114.471956286233
0.731564.02462347642116.617240807699
0.741599.46892450471119.304473967791
0.751636.12182549315122.035564261547
0.761673.87857671258123.937043566545
0.771712.43790049709124.255870555491
0.781751.40120488108122.850015008429
0.791790.44886351016120.314856376272
0.81829.49435415736117.728526588533
0.811868.7192781235116.041019567391
0.821908.45925501724115.517294624561
0.831949.00555824887115.621062668986
0.841990.44795384082115.412016720203
0.852032.6598021824114.210264175407
0.862075.41575858908111.971862776962
0.872118.50537148059109.074528458793
0.882161.68148361584105.547518488324
0.892204.43715004436100.515686900737
0.92245.8708358719192.7872985776783
0.912285.1027677539482.5263569437381
0.922322.7297799128973.4576906833943
0.932363.4753048482875.462023239237
0.942418.73354149713102.598807780824
0.952504.50371279231155.238559957683
0.962629.19179337077203.448534337802
0.972776.79353351124199.659890101839
0.982910.32311253275133.315474673057
0.993010.1909558843967.0485223422989
13075NA

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0 & 131 & NA \tabularnewline
0.01 & 140.952935129619 & 12.8336551828616 \tabularnewline
0.02 & 159.086857602518 & 22.8211264089535 \tabularnewline
0.03 & 180.104456007747 & 25.7211792050035 \tabularnewline
0.04 & 199.745186829536 & 25.4241340775403 \tabularnewline
0.05 & 217.959932677874 & 29.6788346696233 \tabularnewline
0.06 & 237.204794664328 & 37.4374100942633 \tabularnewline
0.07 & 258.76626648746 & 44.4710255131616 \tabularnewline
0.08 & 282.148035006945 & 49.0490005440849 \tabularnewline
0.09 & 306.309990885299 & 51.9228646029555 \tabularnewline
0.1 & 330.590621808212 & 54.2834506070477 \tabularnewline
0.11 & 354.766136545607 & 56.4253446639288 \tabularnewline
0.12 & 378.734768766922 & 57.9962324318456 \tabularnewline
0.13 & 402.316914880323 & 58.6873059622645 \tabularnewline
0.14 & 425.269116180556 & 58.4991067772105 \tabularnewline
0.15 & 447.383164653525 & 57.6770917203172 \tabularnewline
0.16 & 468.555879516831 & 56.5779010625624 \tabularnewline
0.17 & 488.79825832813 & 55.5164671521427 \tabularnewline
0.18 & 508.201684492505 & 54.6550984984757 \tabularnewline
0.19 & 526.893090433808 & 54.028398049342 \tabularnewline
0.2 & 545.005190418686 & 53.6393116744142 \tabularnewline
0.21 & 562.668993151068 & 53.5344643747961 \tabularnewline
0.22 & 580.01769634576 & 53.7761545572391 \tabularnewline
0.23 & 597.187417066698 & 54.3950746282738 \tabularnewline
0.24 & 614.309324318766 & 55.3716159270503 \tabularnewline
0.25 & 631.497135433368 & 56.6297297526944 \tabularnewline
0.26 & 648.835598274782 & 58.0684551511121 \tabularnewline
0.27 & 666.371591996889 & 59.5538356005848 \tabularnewline
0.28 & 684.106118251192 & 60.9224646342083 \tabularnewline
0.29 & 701.98624632915 & 61.9685855386125 \tabularnewline
0.3 & 719.900005918219 & 62.4725470332296 \tabularnewline
0.31 & 737.680726547248 & 62.2317568501044 \tabularnewline
0.32 & 755.127033660703 & 61.1491090202462 \tabularnewline
0.33 & 772.039594683795 & 59.2950592078298 \tabularnewline
0.34 & 788.267906974505 & 56.9383166645049 \tabularnewline
0.35 & 803.75409830561 & 54.5094082521647 \tabularnewline
0.36 & 818.559382621872 & 52.5159382831688 \tabularnewline
0.37 & 832.863131287213 & 51.4077044851596 \tabularnewline
0.38 & 846.932290109606 & 51.4665891632158 \tabularnewline
0.39 & 861.066990378203 & 52.7078700625834 \tabularnewline
0.4 & 875.534514759382 & 54.8562729743364 \tabularnewline
0.41 & 890.507378055565 & 57.4064804207712 \tabularnewline
0.42 & 906.021630722117 & 59.7460062716682 \tabularnewline
0.43 & 921.967911256942 & 61.3048608047424 \tabularnewline
0.44 & 938.120103761415 & 61.7162949345843 \tabularnewline
0.45 & 954.196143988484 & 60.8996310502328 \tabularnewline
0.46 & 969.9357414395 & 59.1086519912785 \tabularnewline
0.47 & 985.174160991995 & 56.8647705442502 \tabularnewline
0.48 & 999.891940111877 & 54.8347070489273 \tabularnewline
0.49 & 1014.22726911347 & 53.6678686280485 \tabularnewline
0.5 & 1028.448393264 & 53.8219433817037 \tabularnewline
0.51 & 1042.89452804767 & 55.4392707973384 \tabularnewline
0.52 & 1057.9022605584 & 58.3192088099402 \tabularnewline
0.53 & 1073.73783497244 & 62.00347093757 \tabularnewline
0.54 & 1090.55291734384 & 65.9354675155808 \tabularnewline
0.55 & 1108.37309675044 & 69.6198127158458 \tabularnewline
0.56 & 1127.11742733573 & 72.7111399942361 \tabularnewline
0.57 & 1146.6381862878 & 75.0748087826637 \tabularnewline
0.58 & 1166.7666183952 & 76.7380123481258 \tabularnewline
0.59 & 1187.35371359333 & 77.864205320189 \tabularnewline
0.6 & 1208.30202741625 & 78.6756993192204 \tabularnewline
0.61 & 1229.58987075836 & 79.4859852516927 \tabularnewline
0.62 & 1251.28880584208 & 80.6555947722188 \tabularnewline
0.63 & 1273.56979907064 & 82.5737555616552 \tabularnewline
0.64 & 1296.68803443068 & 85.5514706596488 \tabularnewline
0.65 & 1320.93817812819 & 89.6495131075636 \tabularnewline
0.66 & 1346.58374210589 & 94.5984736712832 \tabularnewline
0.67 & 1373.78149437558 & 99.7935103160467 \tabularnewline
0.68 & 1402.53376999254 & 104.537795340311 \tabularnewline
0.69 & 1432.69733645091 & 108.285847755927 \tabularnewline
0.7 & 1464.05431574176 & 110.910062833217 \tabularnewline
0.71 & 1496.41763066661 & 112.758272161617 \tabularnewline
0.72 & 1529.71853874514 & 114.471956286233 \tabularnewline
0.73 & 1564.02462347642 & 116.617240807699 \tabularnewline
0.74 & 1599.46892450471 & 119.304473967791 \tabularnewline
0.75 & 1636.12182549315 & 122.035564261547 \tabularnewline
0.76 & 1673.87857671258 & 123.937043566545 \tabularnewline
0.77 & 1712.43790049709 & 124.255870555491 \tabularnewline
0.78 & 1751.40120488108 & 122.850015008429 \tabularnewline
0.79 & 1790.44886351016 & 120.314856376272 \tabularnewline
0.8 & 1829.49435415736 & 117.728526588533 \tabularnewline
0.81 & 1868.7192781235 & 116.041019567391 \tabularnewline
0.82 & 1908.45925501724 & 115.517294624561 \tabularnewline
0.83 & 1949.00555824887 & 115.621062668986 \tabularnewline
0.84 & 1990.44795384082 & 115.412016720203 \tabularnewline
0.85 & 2032.6598021824 & 114.210264175407 \tabularnewline
0.86 & 2075.41575858908 & 111.971862776962 \tabularnewline
0.87 & 2118.50537148059 & 109.074528458793 \tabularnewline
0.88 & 2161.68148361584 & 105.547518488324 \tabularnewline
0.89 & 2204.43715004436 & 100.515686900737 \tabularnewline
0.9 & 2245.87083587191 & 92.7872985776783 \tabularnewline
0.91 & 2285.10276775394 & 82.5263569437381 \tabularnewline
0.92 & 2322.72977991289 & 73.4576906833943 \tabularnewline
0.93 & 2363.47530484828 & 75.462023239237 \tabularnewline
0.94 & 2418.73354149713 & 102.598807780824 \tabularnewline
0.95 & 2504.50371279231 & 155.238559957683 \tabularnewline
0.96 & 2629.19179337077 & 203.448534337802 \tabularnewline
0.97 & 2776.79353351124 & 199.659890101839 \tabularnewline
0.98 & 2910.32311253275 & 133.315474673057 \tabularnewline
0.99 & 3010.19095588439 & 67.0485223422989 \tabularnewline
1 & 3075 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=281453&T=1

[TABLE]
[ROW][C]Harrell-Davis Quantiles[/C][/ROW]
[ROW][C]quantiles[/C][C]value[/C][C]standard error[/C][/ROW]
[ROW][C]0[/C][C]131[/C][C]NA[/C][/ROW]
[ROW][C]0.01[/C][C]140.952935129619[/C][C]12.8336551828616[/C][/ROW]
[ROW][C]0.02[/C][C]159.086857602518[/C][C]22.8211264089535[/C][/ROW]
[ROW][C]0.03[/C][C]180.104456007747[/C][C]25.7211792050035[/C][/ROW]
[ROW][C]0.04[/C][C]199.745186829536[/C][C]25.4241340775403[/C][/ROW]
[ROW][C]0.05[/C][C]217.959932677874[/C][C]29.6788346696233[/C][/ROW]
[ROW][C]0.06[/C][C]237.204794664328[/C][C]37.4374100942633[/C][/ROW]
[ROW][C]0.07[/C][C]258.76626648746[/C][C]44.4710255131616[/C][/ROW]
[ROW][C]0.08[/C][C]282.148035006945[/C][C]49.0490005440849[/C][/ROW]
[ROW][C]0.09[/C][C]306.309990885299[/C][C]51.9228646029555[/C][/ROW]
[ROW][C]0.1[/C][C]330.590621808212[/C][C]54.2834506070477[/C][/ROW]
[ROW][C]0.11[/C][C]354.766136545607[/C][C]56.4253446639288[/C][/ROW]
[ROW][C]0.12[/C][C]378.734768766922[/C][C]57.9962324318456[/C][/ROW]
[ROW][C]0.13[/C][C]402.316914880323[/C][C]58.6873059622645[/C][/ROW]
[ROW][C]0.14[/C][C]425.269116180556[/C][C]58.4991067772105[/C][/ROW]
[ROW][C]0.15[/C][C]447.383164653525[/C][C]57.6770917203172[/C][/ROW]
[ROW][C]0.16[/C][C]468.555879516831[/C][C]56.5779010625624[/C][/ROW]
[ROW][C]0.17[/C][C]488.79825832813[/C][C]55.5164671521427[/C][/ROW]
[ROW][C]0.18[/C][C]508.201684492505[/C][C]54.6550984984757[/C][/ROW]
[ROW][C]0.19[/C][C]526.893090433808[/C][C]54.028398049342[/C][/ROW]
[ROW][C]0.2[/C][C]545.005190418686[/C][C]53.6393116744142[/C][/ROW]
[ROW][C]0.21[/C][C]562.668993151068[/C][C]53.5344643747961[/C][/ROW]
[ROW][C]0.22[/C][C]580.01769634576[/C][C]53.7761545572391[/C][/ROW]
[ROW][C]0.23[/C][C]597.187417066698[/C][C]54.3950746282738[/C][/ROW]
[ROW][C]0.24[/C][C]614.309324318766[/C][C]55.3716159270503[/C][/ROW]
[ROW][C]0.25[/C][C]631.497135433368[/C][C]56.6297297526944[/C][/ROW]
[ROW][C]0.26[/C][C]648.835598274782[/C][C]58.0684551511121[/C][/ROW]
[ROW][C]0.27[/C][C]666.371591996889[/C][C]59.5538356005848[/C][/ROW]
[ROW][C]0.28[/C][C]684.106118251192[/C][C]60.9224646342083[/C][/ROW]
[ROW][C]0.29[/C][C]701.98624632915[/C][C]61.9685855386125[/C][/ROW]
[ROW][C]0.3[/C][C]719.900005918219[/C][C]62.4725470332296[/C][/ROW]
[ROW][C]0.31[/C][C]737.680726547248[/C][C]62.2317568501044[/C][/ROW]
[ROW][C]0.32[/C][C]755.127033660703[/C][C]61.1491090202462[/C][/ROW]
[ROW][C]0.33[/C][C]772.039594683795[/C][C]59.2950592078298[/C][/ROW]
[ROW][C]0.34[/C][C]788.267906974505[/C][C]56.9383166645049[/C][/ROW]
[ROW][C]0.35[/C][C]803.75409830561[/C][C]54.5094082521647[/C][/ROW]
[ROW][C]0.36[/C][C]818.559382621872[/C][C]52.5159382831688[/C][/ROW]
[ROW][C]0.37[/C][C]832.863131287213[/C][C]51.4077044851596[/C][/ROW]
[ROW][C]0.38[/C][C]846.932290109606[/C][C]51.4665891632158[/C][/ROW]
[ROW][C]0.39[/C][C]861.066990378203[/C][C]52.7078700625834[/C][/ROW]
[ROW][C]0.4[/C][C]875.534514759382[/C][C]54.8562729743364[/C][/ROW]
[ROW][C]0.41[/C][C]890.507378055565[/C][C]57.4064804207712[/C][/ROW]
[ROW][C]0.42[/C][C]906.021630722117[/C][C]59.7460062716682[/C][/ROW]
[ROW][C]0.43[/C][C]921.967911256942[/C][C]61.3048608047424[/C][/ROW]
[ROW][C]0.44[/C][C]938.120103761415[/C][C]61.7162949345843[/C][/ROW]
[ROW][C]0.45[/C][C]954.196143988484[/C][C]60.8996310502328[/C][/ROW]
[ROW][C]0.46[/C][C]969.9357414395[/C][C]59.1086519912785[/C][/ROW]
[ROW][C]0.47[/C][C]985.174160991995[/C][C]56.8647705442502[/C][/ROW]
[ROW][C]0.48[/C][C]999.891940111877[/C][C]54.8347070489273[/C][/ROW]
[ROW][C]0.49[/C][C]1014.22726911347[/C][C]53.6678686280485[/C][/ROW]
[ROW][C]0.5[/C][C]1028.448393264[/C][C]53.8219433817037[/C][/ROW]
[ROW][C]0.51[/C][C]1042.89452804767[/C][C]55.4392707973384[/C][/ROW]
[ROW][C]0.52[/C][C]1057.9022605584[/C][C]58.3192088099402[/C][/ROW]
[ROW][C]0.53[/C][C]1073.73783497244[/C][C]62.00347093757[/C][/ROW]
[ROW][C]0.54[/C][C]1090.55291734384[/C][C]65.9354675155808[/C][/ROW]
[ROW][C]0.55[/C][C]1108.37309675044[/C][C]69.6198127158458[/C][/ROW]
[ROW][C]0.56[/C][C]1127.11742733573[/C][C]72.7111399942361[/C][/ROW]
[ROW][C]0.57[/C][C]1146.6381862878[/C][C]75.0748087826637[/C][/ROW]
[ROW][C]0.58[/C][C]1166.7666183952[/C][C]76.7380123481258[/C][/ROW]
[ROW][C]0.59[/C][C]1187.35371359333[/C][C]77.864205320189[/C][/ROW]
[ROW][C]0.6[/C][C]1208.30202741625[/C][C]78.6756993192204[/C][/ROW]
[ROW][C]0.61[/C][C]1229.58987075836[/C][C]79.4859852516927[/C][/ROW]
[ROW][C]0.62[/C][C]1251.28880584208[/C][C]80.6555947722188[/C][/ROW]
[ROW][C]0.63[/C][C]1273.56979907064[/C][C]82.5737555616552[/C][/ROW]
[ROW][C]0.64[/C][C]1296.68803443068[/C][C]85.5514706596488[/C][/ROW]
[ROW][C]0.65[/C][C]1320.93817812819[/C][C]89.6495131075636[/C][/ROW]
[ROW][C]0.66[/C][C]1346.58374210589[/C][C]94.5984736712832[/C][/ROW]
[ROW][C]0.67[/C][C]1373.78149437558[/C][C]99.7935103160467[/C][/ROW]
[ROW][C]0.68[/C][C]1402.53376999254[/C][C]104.537795340311[/C][/ROW]
[ROW][C]0.69[/C][C]1432.69733645091[/C][C]108.285847755927[/C][/ROW]
[ROW][C]0.7[/C][C]1464.05431574176[/C][C]110.910062833217[/C][/ROW]
[ROW][C]0.71[/C][C]1496.41763066661[/C][C]112.758272161617[/C][/ROW]
[ROW][C]0.72[/C][C]1529.71853874514[/C][C]114.471956286233[/C][/ROW]
[ROW][C]0.73[/C][C]1564.02462347642[/C][C]116.617240807699[/C][/ROW]
[ROW][C]0.74[/C][C]1599.46892450471[/C][C]119.304473967791[/C][/ROW]
[ROW][C]0.75[/C][C]1636.12182549315[/C][C]122.035564261547[/C][/ROW]
[ROW][C]0.76[/C][C]1673.87857671258[/C][C]123.937043566545[/C][/ROW]
[ROW][C]0.77[/C][C]1712.43790049709[/C][C]124.255870555491[/C][/ROW]
[ROW][C]0.78[/C][C]1751.40120488108[/C][C]122.850015008429[/C][/ROW]
[ROW][C]0.79[/C][C]1790.44886351016[/C][C]120.314856376272[/C][/ROW]
[ROW][C]0.8[/C][C]1829.49435415736[/C][C]117.728526588533[/C][/ROW]
[ROW][C]0.81[/C][C]1868.7192781235[/C][C]116.041019567391[/C][/ROW]
[ROW][C]0.82[/C][C]1908.45925501724[/C][C]115.517294624561[/C][/ROW]
[ROW][C]0.83[/C][C]1949.00555824887[/C][C]115.621062668986[/C][/ROW]
[ROW][C]0.84[/C][C]1990.44795384082[/C][C]115.412016720203[/C][/ROW]
[ROW][C]0.85[/C][C]2032.6598021824[/C][C]114.210264175407[/C][/ROW]
[ROW][C]0.86[/C][C]2075.41575858908[/C][C]111.971862776962[/C][/ROW]
[ROW][C]0.87[/C][C]2118.50537148059[/C][C]109.074528458793[/C][/ROW]
[ROW][C]0.88[/C][C]2161.68148361584[/C][C]105.547518488324[/C][/ROW]
[ROW][C]0.89[/C][C]2204.43715004436[/C][C]100.515686900737[/C][/ROW]
[ROW][C]0.9[/C][C]2245.87083587191[/C][C]92.7872985776783[/C][/ROW]
[ROW][C]0.91[/C][C]2285.10276775394[/C][C]82.5263569437381[/C][/ROW]
[ROW][C]0.92[/C][C]2322.72977991289[/C][C]73.4576906833943[/C][/ROW]
[ROW][C]0.93[/C][C]2363.47530484828[/C][C]75.462023239237[/C][/ROW]
[ROW][C]0.94[/C][C]2418.73354149713[/C][C]102.598807780824[/C][/ROW]
[ROW][C]0.95[/C][C]2504.50371279231[/C][C]155.238559957683[/C][/ROW]
[ROW][C]0.96[/C][C]2629.19179337077[/C][C]203.448534337802[/C][/ROW]
[ROW][C]0.97[/C][C]2776.79353351124[/C][C]199.659890101839[/C][/ROW]
[ROW][C]0.98[/C][C]2910.32311253275[/C][C]133.315474673057[/C][/ROW]
[ROW][C]0.99[/C][C]3010.19095588439[/C][C]67.0485223422989[/C][/ROW]
[ROW][C]1[/C][C]3075[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=281453&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=281453&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Harrell-Davis Quantiles
quantilesvaluestandard error
0131NA
0.01140.95293512961912.8336551828616
0.02159.08685760251822.8211264089535
0.03180.10445600774725.7211792050035
0.04199.74518682953625.4241340775403
0.05217.95993267787429.6788346696233
0.06237.20479466432837.4374100942633
0.07258.7662664874644.4710255131616
0.08282.14803500694549.0490005440849
0.09306.30999088529951.9228646029555
0.1330.59062180821254.2834506070477
0.11354.76613654560756.4253446639288
0.12378.73476876692257.9962324318456
0.13402.31691488032358.6873059622645
0.14425.26911618055658.4991067772105
0.15447.38316465352557.6770917203172
0.16468.55587951683156.5779010625624
0.17488.7982583281355.5164671521427
0.18508.20168449250554.6550984984757
0.19526.89309043380854.028398049342
0.2545.00519041868653.6393116744142
0.21562.66899315106853.5344643747961
0.22580.0176963457653.7761545572391
0.23597.18741706669854.3950746282738
0.24614.30932431876655.3716159270503
0.25631.49713543336856.6297297526944
0.26648.83559827478258.0684551511121
0.27666.37159199688959.5538356005848
0.28684.10611825119260.9224646342083
0.29701.9862463291561.9685855386125
0.3719.90000591821962.4725470332296
0.31737.68072654724862.2317568501044
0.32755.12703366070361.1491090202462
0.33772.03959468379559.2950592078298
0.34788.26790697450556.9383166645049
0.35803.7540983056154.5094082521647
0.36818.55938262187252.5159382831688
0.37832.86313128721351.4077044851596
0.38846.93229010960651.4665891632158
0.39861.06699037820352.7078700625834
0.4875.53451475938254.8562729743364
0.41890.50737805556557.4064804207712
0.42906.02163072211759.7460062716682
0.43921.96791125694261.3048608047424
0.44938.12010376141561.7162949345843
0.45954.19614398848460.8996310502328
0.46969.935741439559.1086519912785
0.47985.17416099199556.8647705442502
0.48999.89194011187754.8347070489273
0.491014.2272691134753.6678686280485
0.51028.44839326453.8219433817037
0.511042.8945280476755.4392707973384
0.521057.902260558458.3192088099402
0.531073.7378349724462.00347093757
0.541090.5529173438465.9354675155808
0.551108.3730967504469.6198127158458
0.561127.1174273357372.7111399942361
0.571146.638186287875.0748087826637
0.581166.766618395276.7380123481258
0.591187.3537135933377.864205320189
0.61208.3020274162578.6756993192204
0.611229.5898707583679.4859852516927
0.621251.2888058420880.6555947722188
0.631273.5697990706482.5737555616552
0.641296.6880344306885.5514706596488
0.651320.9381781281989.6495131075636
0.661346.5837421058994.5984736712832
0.671373.7814943755899.7935103160467
0.681402.53376999254104.537795340311
0.691432.69733645091108.285847755927
0.71464.05431574176110.910062833217
0.711496.41763066661112.758272161617
0.721529.71853874514114.471956286233
0.731564.02462347642116.617240807699
0.741599.46892450471119.304473967791
0.751636.12182549315122.035564261547
0.761673.87857671258123.937043566545
0.771712.43790049709124.255870555491
0.781751.40120488108122.850015008429
0.791790.44886351016120.314856376272
0.81829.49435415736117.728526588533
0.811868.7192781235116.041019567391
0.821908.45925501724115.517294624561
0.831949.00555824887115.621062668986
0.841990.44795384082115.412016720203
0.852032.6598021824114.210264175407
0.862075.41575858908111.971862776962
0.872118.50537148059109.074528458793
0.882161.68148361584105.547518488324
0.892204.43715004436100.515686900737
0.92245.8708358719192.7872985776783
0.912285.1027677539482.5263569437381
0.922322.7297799128973.4576906833943
0.932363.4753048482875.462023239237
0.942418.73354149713102.598807780824
0.952504.50371279231155.238559957683
0.962629.19179337077203.448534337802
0.972776.79353351124199.659890101839
0.982910.32311253275133.315474673057
0.993010.1909558843967.0485223422989
13075NA



Parameters (Session):
par1 = 0.1 ; par2 = 0.9 ; par3 = 0.1 ;
Parameters (R input):
par1 = 0 ; par2 = 1 ; par3 = 0.01 ;
R code (references can be found in the software module):
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')