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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationSun, 29 Jul 2012 06:32:31 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Jul/29/t1343558036nfspbadlal2e267.htm/, Retrieved Wed, 01 May 2024 20:25:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168936, Retrieved Wed, 01 May 2024 20:25:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsBart Mortelmans
Estimated Impact155

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Tijdreeks 2 - Stap 1] [2012-07-29 10:04:17] [f85cc8f00ef4b762f0a6fdfddc793773]
- RMP   [Harrell-Davis Quantiles] [Tijdreeks 2 - Stap 5] [2012-07-29 10:30:29] [226376a35b8869827dc57271384c00a4]
- R P       [Harrell-Davis Quantiles] [Tijdreeks 2 - Stap 6] [2012-07-29 10:32:31] [480fcaba71e70207c3e0ad7177944aa6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
940
950
920
930
930
900
940
840
890
850
830
940
960
900
940
920
930
970
930
780
810
870
720
880
920
920
950
950
890
960
780
780
760
860
740
1020
890
1040
920
900
950
990
840
740
840
960
790
1010
900
970
920
980
890
1000
880
740
860
940
760
1010
870
980
920
950
880
980
910
730
880
820
690
990
800
960
910
950
940
1010
890
660
860
840
740
980
820
1080
930
970
930
1010
880
740
860
810
750
890
790
1000
890
970
900
990
910
730
850
840
830
950

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168936&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168936&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168936&T=0

As an alternative you can also use a QR Code:  
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'Herman Ole Andreas Wold' @ wold.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01677.38136925110627.6035631350914
0.02699.97028251794622.9256738631441
0.03716.84361937272116.0292307979227
0.04727.26028166548510.5762577835251
0.05733.5828512503427.79685037443661
0.06737.918614369377.19840720437276
0.07741.6339787426858.38461854003852
0.08745.55250653209710.7831011877813
0.09750.10755579885213.5880412462763
0.1755.40991071638416.0933021884926
0.11761.33211665972917.8946504428293
0.12767.63171947340218.933437443445
0.13774.06863918822219.4058624728463
0.14780.47387686376719.5868622532933
0.15786.76092266404219.679728581561
0.16792.89922314162719.745044297547
0.17798.87738667278419.729367828554
0.18804.67659728448219.5412462206893
0.19810.26184432368319.1139370918
0.2815.58808528186818.4390229501106
0.21820.61367845557117.5686390511211
0.22825.31362040516916.5969835033874
0.23829.68779827316715.6416452665132
0.24833.76244788050814.812937260289
0.25837.58529363478714.1938728253212
0.26841.21630338485613.8197231440907
0.27844.71672365491913.6714155161915
0.28848.13908994572613.6892534327638
0.29851.52025847678313.7911755561148
0.3854.87839475419513.8939167232858
0.31858.21369103009113.9312556097117
0.32861.51177916944613.856668707942
0.33864.74854926558913.643338129417
0.34867.89528534795513.2835649923994
0.35870.92342646208212.7890094089179
0.36873.80860851950612.1852798980277
0.37876.5338299074811.5096358121163
0.38879.0916395496410.8117377213923
0.39881.48525684566410.1405841354942
0.4883.7285658554139.54646659373062
0.41885.8449984919239.07317198703499
0.42887.8654164772538.75291077403106
0.43889.8251967852218.60247068096803
0.44891.760806264468.62013411874499
0.45893.7062107635678.78653674082768
0.46895.6894961225619.06310920742021
0.47897.7300776748569.40325664959477
0.48899.8368399933389.75204364388867
0.49902.0074799625810.0558790003853
0.5904.22921973226610.2698888873483
0.51906.4809011963110.3596395822754
0.52908.7362649643310.3081995804954
0.53910.96797507907610.1204368423196
0.54913.1517361003299.81957863574087
0.55915.2697486759279.44697989004616
0.56917.3128370909939.0493972919534
0.57919.280870061038.67266204731013
0.58921.1815115413738.3528671158268
0.59923.0277446455328.10748642527214
0.6924.8348673905847.93827455238671
0.61926.6176839632517.83322630468896
0.62928.3884257731517.77305803472039
0.63930.1556299178177.73795600495148
0.64931.9239047394297.70983828401042
0.65933.6943218948547.67465696875548
0.66935.4651336508097.6223526722409
0.67937.232607958347.54579983474587
0.68938.9919450704647.44374497580331
0.69940.7384020615857.3163402887734
0.7942.4688062522577.17134535044948
0.71944.1835071029527.02282063020681
0.72945.8884984779286.89633125294183
0.73947.5970632634466.82654953914269
0.74949.3300786340786.84875988591181
0.75951.1142935692026.98716297547114
0.76952.9785052752237.24164171973235
0.77954.9484117013547.58308245160527
0.78957.0416004780027.96145405366941
0.79959.2642693823028.3197074866608
0.8961.6107457900188.61030342607291
0.81964.0659346268328.80306287870848
0.82966.6099556580398.89140879778499
0.83969.2238305563088.88829154761668
0.84971.8951955739448.82423166405643
0.85974.6233236402058.74019532787523
0.86977.4228158092588.68711734112475
0.87980.3249544426838.71471694259644
0.88983.3749374444168.85587011832447
0.89986.6222052229249.10796324792339
0.9990.1006413962099.40638119412145
0.91993.7985487134799.60431799762907
0.92997.6306543737159.47734049589985
0.931001.449422166238.8253780793301
0.941005.159525582437.70944871936195
0.951008.993346418566.82809449814211
0.961013.936619940547.82326923279763
0.971022.189269393512.1385011499579
0.981037.1588103172319.7349387268548
0.991060.1646210460730.1985522113981

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 677.381369251106 & 27.6035631350914 \tabularnewline
0.02 & 699.970282517946 & 22.9256738631441 \tabularnewline
0.03 & 716.843619372721 & 16.0292307979227 \tabularnewline
0.04 & 727.260281665485 & 10.5762577835251 \tabularnewline
0.05 & 733.582851250342 & 7.79685037443661 \tabularnewline
0.06 & 737.91861436937 & 7.19840720437276 \tabularnewline
0.07 & 741.633978742685 & 8.38461854003852 \tabularnewline
0.08 & 745.552506532097 & 10.7831011877813 \tabularnewline
0.09 & 750.107555798852 & 13.5880412462763 \tabularnewline
0.1 & 755.409910716384 & 16.0933021884926 \tabularnewline
0.11 & 761.332116659729 & 17.8946504428293 \tabularnewline
0.12 & 767.631719473402 & 18.933437443445 \tabularnewline
0.13 & 774.068639188222 & 19.4058624728463 \tabularnewline
0.14 & 780.473876863767 & 19.5868622532933 \tabularnewline
0.15 & 786.760922664042 & 19.679728581561 \tabularnewline
0.16 & 792.899223141627 & 19.745044297547 \tabularnewline
0.17 & 798.877386672784 & 19.729367828554 \tabularnewline
0.18 & 804.676597284482 & 19.5412462206893 \tabularnewline
0.19 & 810.261844323683 & 19.1139370918 \tabularnewline
0.2 & 815.588085281868 & 18.4390229501106 \tabularnewline
0.21 & 820.613678455571 & 17.5686390511211 \tabularnewline
0.22 & 825.313620405169 & 16.5969835033874 \tabularnewline
0.23 & 829.687798273167 & 15.6416452665132 \tabularnewline
0.24 & 833.762447880508 & 14.812937260289 \tabularnewline
0.25 & 837.585293634787 & 14.1938728253212 \tabularnewline
0.26 & 841.216303384856 & 13.8197231440907 \tabularnewline
0.27 & 844.716723654919 & 13.6714155161915 \tabularnewline
0.28 & 848.139089945726 & 13.6892534327638 \tabularnewline
0.29 & 851.520258476783 & 13.7911755561148 \tabularnewline
0.3 & 854.878394754195 & 13.8939167232858 \tabularnewline
0.31 & 858.213691030091 & 13.9312556097117 \tabularnewline
0.32 & 861.511779169446 & 13.856668707942 \tabularnewline
0.33 & 864.748549265589 & 13.643338129417 \tabularnewline
0.34 & 867.895285347955 & 13.2835649923994 \tabularnewline
0.35 & 870.923426462082 & 12.7890094089179 \tabularnewline
0.36 & 873.808608519506 & 12.1852798980277 \tabularnewline
0.37 & 876.53382990748 & 11.5096358121163 \tabularnewline
0.38 & 879.09163954964 & 10.8117377213923 \tabularnewline
0.39 & 881.485256845664 & 10.1405841354942 \tabularnewline
0.4 & 883.728565855413 & 9.54646659373062 \tabularnewline
0.41 & 885.844998491923 & 9.07317198703499 \tabularnewline
0.42 & 887.865416477253 & 8.75291077403106 \tabularnewline
0.43 & 889.825196785221 & 8.60247068096803 \tabularnewline
0.44 & 891.76080626446 & 8.62013411874499 \tabularnewline
0.45 & 893.706210763567 & 8.78653674082768 \tabularnewline
0.46 & 895.689496122561 & 9.06310920742021 \tabularnewline
0.47 & 897.730077674856 & 9.40325664959477 \tabularnewline
0.48 & 899.836839993338 & 9.75204364388867 \tabularnewline
0.49 & 902.00747996258 & 10.0558790003853 \tabularnewline
0.5 & 904.229219732266 & 10.2698888873483 \tabularnewline
0.51 & 906.48090119631 & 10.3596395822754 \tabularnewline
0.52 & 908.73626496433 & 10.3081995804954 \tabularnewline
0.53 & 910.967975079076 & 10.1204368423196 \tabularnewline
0.54 & 913.151736100329 & 9.81957863574087 \tabularnewline
0.55 & 915.269748675927 & 9.44697989004616 \tabularnewline
0.56 & 917.312837090993 & 9.0493972919534 \tabularnewline
0.57 & 919.28087006103 & 8.67266204731013 \tabularnewline
0.58 & 921.181511541373 & 8.3528671158268 \tabularnewline
0.59 & 923.027744645532 & 8.10748642527214 \tabularnewline
0.6 & 924.834867390584 & 7.93827455238671 \tabularnewline
0.61 & 926.617683963251 & 7.83322630468896 \tabularnewline
0.62 & 928.388425773151 & 7.77305803472039 \tabularnewline
0.63 & 930.155629917817 & 7.73795600495148 \tabularnewline
0.64 & 931.923904739429 & 7.70983828401042 \tabularnewline
0.65 & 933.694321894854 & 7.67465696875548 \tabularnewline
0.66 & 935.465133650809 & 7.6223526722409 \tabularnewline
0.67 & 937.23260795834 & 7.54579983474587 \tabularnewline
0.68 & 938.991945070464 & 7.44374497580331 \tabularnewline
0.69 & 940.738402061585 & 7.3163402887734 \tabularnewline
0.7 & 942.468806252257 & 7.17134535044948 \tabularnewline
0.71 & 944.183507102952 & 7.02282063020681 \tabularnewline
0.72 & 945.888498477928 & 6.89633125294183 \tabularnewline
0.73 & 947.597063263446 & 6.82654953914269 \tabularnewline
0.74 & 949.330078634078 & 6.84875988591181 \tabularnewline
0.75 & 951.114293569202 & 6.98716297547114 \tabularnewline
0.76 & 952.978505275223 & 7.24164171973235 \tabularnewline
0.77 & 954.948411701354 & 7.58308245160527 \tabularnewline
0.78 & 957.041600478002 & 7.96145405366941 \tabularnewline
0.79 & 959.264269382302 & 8.3197074866608 \tabularnewline
0.8 & 961.610745790018 & 8.61030342607291 \tabularnewline
0.81 & 964.065934626832 & 8.80306287870848 \tabularnewline
0.82 & 966.609955658039 & 8.89140879778499 \tabularnewline
0.83 & 969.223830556308 & 8.88829154761668 \tabularnewline
0.84 & 971.895195573944 & 8.82423166405643 \tabularnewline
0.85 & 974.623323640205 & 8.74019532787523 \tabularnewline
0.86 & 977.422815809258 & 8.68711734112475 \tabularnewline
0.87 & 980.324954442683 & 8.71471694259644 \tabularnewline
0.88 & 983.374937444416 & 8.85587011832447 \tabularnewline
0.89 & 986.622205222924 & 9.10796324792339 \tabularnewline
0.9 & 990.100641396209 & 9.40638119412145 \tabularnewline
0.91 & 993.798548713479 & 9.60431799762907 \tabularnewline
0.92 & 997.630654373715 & 9.47734049589985 \tabularnewline
0.93 & 1001.44942216623 & 8.8253780793301 \tabularnewline
0.94 & 1005.15952558243 & 7.70944871936195 \tabularnewline
0.95 & 1008.99334641856 & 6.82809449814211 \tabularnewline
0.96 & 1013.93661994054 & 7.82326923279763 \tabularnewline
0.97 & 1022.1892693935 & 12.1385011499579 \tabularnewline
0.98 & 1037.15881031723 & 19.7349387268548 \tabularnewline
0.99 & 1060.16462104607 & 30.1985522113981 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168936&T=1

[TABLE]
[ROW][C]Harrell-Davis Quantiles[/C][/ROW]
[ROW][C]quantiles[/C][C]value[/C][C]standard error[/C][/ROW]
[ROW][C]0.01[/C][C]677.381369251106[/C][C]27.6035631350914[/C][/ROW]
[ROW][C]0.02[/C][C]699.970282517946[/C][C]22.9256738631441[/C][/ROW]
[ROW][C]0.03[/C][C]716.843619372721[/C][C]16.0292307979227[/C][/ROW]
[ROW][C]0.04[/C][C]727.260281665485[/C][C]10.5762577835251[/C][/ROW]
[ROW][C]0.05[/C][C]733.582851250342[/C][C]7.79685037443661[/C][/ROW]
[ROW][C]0.06[/C][C]737.91861436937[/C][C]7.19840720437276[/C][/ROW]
[ROW][C]0.07[/C][C]741.633978742685[/C][C]8.38461854003852[/C][/ROW]
[ROW][C]0.08[/C][C]745.552506532097[/C][C]10.7831011877813[/C][/ROW]
[ROW][C]0.09[/C][C]750.107555798852[/C][C]13.5880412462763[/C][/ROW]
[ROW][C]0.1[/C][C]755.409910716384[/C][C]16.0933021884926[/C][/ROW]
[ROW][C]0.11[/C][C]761.332116659729[/C][C]17.8946504428293[/C][/ROW]
[ROW][C]0.12[/C][C]767.631719473402[/C][C]18.933437443445[/C][/ROW]
[ROW][C]0.13[/C][C]774.068639188222[/C][C]19.4058624728463[/C][/ROW]
[ROW][C]0.14[/C][C]780.473876863767[/C][C]19.5868622532933[/C][/ROW]
[ROW][C]0.15[/C][C]786.760922664042[/C][C]19.679728581561[/C][/ROW]
[ROW][C]0.16[/C][C]792.899223141627[/C][C]19.745044297547[/C][/ROW]
[ROW][C]0.17[/C][C]798.877386672784[/C][C]19.729367828554[/C][/ROW]
[ROW][C]0.18[/C][C]804.676597284482[/C][C]19.5412462206893[/C][/ROW]
[ROW][C]0.19[/C][C]810.261844323683[/C][C]19.1139370918[/C][/ROW]
[ROW][C]0.2[/C][C]815.588085281868[/C][C]18.4390229501106[/C][/ROW]
[ROW][C]0.21[/C][C]820.613678455571[/C][C]17.5686390511211[/C][/ROW]
[ROW][C]0.22[/C][C]825.313620405169[/C][C]16.5969835033874[/C][/ROW]
[ROW][C]0.23[/C][C]829.687798273167[/C][C]15.6416452665132[/C][/ROW]
[ROW][C]0.24[/C][C]833.762447880508[/C][C]14.812937260289[/C][/ROW]
[ROW][C]0.25[/C][C]837.585293634787[/C][C]14.1938728253212[/C][/ROW]
[ROW][C]0.26[/C][C]841.216303384856[/C][C]13.8197231440907[/C][/ROW]
[ROW][C]0.27[/C][C]844.716723654919[/C][C]13.6714155161915[/C][/ROW]
[ROW][C]0.28[/C][C]848.139089945726[/C][C]13.6892534327638[/C][/ROW]
[ROW][C]0.29[/C][C]851.520258476783[/C][C]13.7911755561148[/C][/ROW]
[ROW][C]0.3[/C][C]854.878394754195[/C][C]13.8939167232858[/C][/ROW]
[ROW][C]0.31[/C][C]858.213691030091[/C][C]13.9312556097117[/C][/ROW]
[ROW][C]0.32[/C][C]861.511779169446[/C][C]13.856668707942[/C][/ROW]
[ROW][C]0.33[/C][C]864.748549265589[/C][C]13.643338129417[/C][/ROW]
[ROW][C]0.34[/C][C]867.895285347955[/C][C]13.2835649923994[/C][/ROW]
[ROW][C]0.35[/C][C]870.923426462082[/C][C]12.7890094089179[/C][/ROW]
[ROW][C]0.36[/C][C]873.808608519506[/C][C]12.1852798980277[/C][/ROW]
[ROW][C]0.37[/C][C]876.53382990748[/C][C]11.5096358121163[/C][/ROW]
[ROW][C]0.38[/C][C]879.09163954964[/C][C]10.8117377213923[/C][/ROW]
[ROW][C]0.39[/C][C]881.485256845664[/C][C]10.1405841354942[/C][/ROW]
[ROW][C]0.4[/C][C]883.728565855413[/C][C]9.54646659373062[/C][/ROW]
[ROW][C]0.41[/C][C]885.844998491923[/C][C]9.07317198703499[/C][/ROW]
[ROW][C]0.42[/C][C]887.865416477253[/C][C]8.75291077403106[/C][/ROW]
[ROW][C]0.43[/C][C]889.825196785221[/C][C]8.60247068096803[/C][/ROW]
[ROW][C]0.44[/C][C]891.76080626446[/C][C]8.62013411874499[/C][/ROW]
[ROW][C]0.45[/C][C]893.706210763567[/C][C]8.78653674082768[/C][/ROW]
[ROW][C]0.46[/C][C]895.689496122561[/C][C]9.06310920742021[/C][/ROW]
[ROW][C]0.47[/C][C]897.730077674856[/C][C]9.40325664959477[/C][/ROW]
[ROW][C]0.48[/C][C]899.836839993338[/C][C]9.75204364388867[/C][/ROW]
[ROW][C]0.49[/C][C]902.00747996258[/C][C]10.0558790003853[/C][/ROW]
[ROW][C]0.5[/C][C]904.229219732266[/C][C]10.2698888873483[/C][/ROW]
[ROW][C]0.51[/C][C]906.48090119631[/C][C]10.3596395822754[/C][/ROW]
[ROW][C]0.52[/C][C]908.73626496433[/C][C]10.3081995804954[/C][/ROW]
[ROW][C]0.53[/C][C]910.967975079076[/C][C]10.1204368423196[/C][/ROW]
[ROW][C]0.54[/C][C]913.151736100329[/C][C]9.81957863574087[/C][/ROW]
[ROW][C]0.55[/C][C]915.269748675927[/C][C]9.44697989004616[/C][/ROW]
[ROW][C]0.56[/C][C]917.312837090993[/C][C]9.0493972919534[/C][/ROW]
[ROW][C]0.57[/C][C]919.28087006103[/C][C]8.67266204731013[/C][/ROW]
[ROW][C]0.58[/C][C]921.181511541373[/C][C]8.3528671158268[/C][/ROW]
[ROW][C]0.59[/C][C]923.027744645532[/C][C]8.10748642527214[/C][/ROW]
[ROW][C]0.6[/C][C]924.834867390584[/C][C]7.93827455238671[/C][/ROW]
[ROW][C]0.61[/C][C]926.617683963251[/C][C]7.83322630468896[/C][/ROW]
[ROW][C]0.62[/C][C]928.388425773151[/C][C]7.77305803472039[/C][/ROW]
[ROW][C]0.63[/C][C]930.155629917817[/C][C]7.73795600495148[/C][/ROW]
[ROW][C]0.64[/C][C]931.923904739429[/C][C]7.70983828401042[/C][/ROW]
[ROW][C]0.65[/C][C]933.694321894854[/C][C]7.67465696875548[/C][/ROW]
[ROW][C]0.66[/C][C]935.465133650809[/C][C]7.6223526722409[/C][/ROW]
[ROW][C]0.67[/C][C]937.23260795834[/C][C]7.54579983474587[/C][/ROW]
[ROW][C]0.68[/C][C]938.991945070464[/C][C]7.44374497580331[/C][/ROW]
[ROW][C]0.69[/C][C]940.738402061585[/C][C]7.3163402887734[/C][/ROW]
[ROW][C]0.7[/C][C]942.468806252257[/C][C]7.17134535044948[/C][/ROW]
[ROW][C]0.71[/C][C]944.183507102952[/C][C]7.02282063020681[/C][/ROW]
[ROW][C]0.72[/C][C]945.888498477928[/C][C]6.89633125294183[/C][/ROW]
[ROW][C]0.73[/C][C]947.597063263446[/C][C]6.82654953914269[/C][/ROW]
[ROW][C]0.74[/C][C]949.330078634078[/C][C]6.84875988591181[/C][/ROW]
[ROW][C]0.75[/C][C]951.114293569202[/C][C]6.98716297547114[/C][/ROW]
[ROW][C]0.76[/C][C]952.978505275223[/C][C]7.24164171973235[/C][/ROW]
[ROW][C]0.77[/C][C]954.948411701354[/C][C]7.58308245160527[/C][/ROW]
[ROW][C]0.78[/C][C]957.041600478002[/C][C]7.96145405366941[/C][/ROW]
[ROW][C]0.79[/C][C]959.264269382302[/C][C]8.3197074866608[/C][/ROW]
[ROW][C]0.8[/C][C]961.610745790018[/C][C]8.61030342607291[/C][/ROW]
[ROW][C]0.81[/C][C]964.065934626832[/C][C]8.80306287870848[/C][/ROW]
[ROW][C]0.82[/C][C]966.609955658039[/C][C]8.89140879778499[/C][/ROW]
[ROW][C]0.83[/C][C]969.223830556308[/C][C]8.88829154761668[/C][/ROW]
[ROW][C]0.84[/C][C]971.895195573944[/C][C]8.82423166405643[/C][/ROW]
[ROW][C]0.85[/C][C]974.623323640205[/C][C]8.74019532787523[/C][/ROW]
[ROW][C]0.86[/C][C]977.422815809258[/C][C]8.68711734112475[/C][/ROW]
[ROW][C]0.87[/C][C]980.324954442683[/C][C]8.71471694259644[/C][/ROW]
[ROW][C]0.88[/C][C]983.374937444416[/C][C]8.85587011832447[/C][/ROW]
[ROW][C]0.89[/C][C]986.622205222924[/C][C]9.10796324792339[/C][/ROW]
[ROW][C]0.9[/C][C]990.100641396209[/C][C]9.40638119412145[/C][/ROW]
[ROW][C]0.91[/C][C]993.798548713479[/C][C]9.60431799762907[/C][/ROW]
[ROW][C]0.92[/C][C]997.630654373715[/C][C]9.47734049589985[/C][/ROW]
[ROW][C]0.93[/C][C]1001.44942216623[/C][C]8.8253780793301[/C][/ROW]
[ROW][C]0.94[/C][C]1005.15952558243[/C][C]7.70944871936195[/C][/ROW]
[ROW][C]0.95[/C][C]1008.99334641856[/C][C]6.82809449814211[/C][/ROW]
[ROW][C]0.96[/C][C]1013.93661994054[/C][C]7.82326923279763[/C][/ROW]
[ROW][C]0.97[/C][C]1022.1892693935[/C][C]12.1385011499579[/C][/ROW]
[ROW][C]0.98[/C][C]1037.15881031723[/C][C]19.7349387268548[/C][/ROW]
[ROW][C]0.99[/C][C]1060.16462104607[/C][C]30.1985522113981[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168936&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168936&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Harrell-Davis Quantiles
quantilesvaluestandard error
0.01677.38136925110627.6035631350914
0.02699.97028251794622.9256738631441
0.03716.84361937272116.0292307979227
0.04727.26028166548510.5762577835251
0.05733.5828512503427.79685037443661
0.06737.918614369377.19840720437276
0.07741.6339787426858.38461854003852
0.08745.55250653209710.7831011877813
0.09750.10755579885213.5880412462763
0.1755.40991071638416.0933021884926
0.11761.33211665972917.8946504428293
0.12767.63171947340218.933437443445
0.13774.06863918822219.4058624728463
0.14780.47387686376719.5868622532933
0.15786.76092266404219.679728581561
0.16792.89922314162719.745044297547
0.17798.87738667278419.729367828554
0.18804.67659728448219.5412462206893
0.19810.26184432368319.1139370918
0.2815.58808528186818.4390229501106
0.21820.61367845557117.5686390511211
0.22825.31362040516916.5969835033874
0.23829.68779827316715.6416452665132
0.24833.76244788050814.812937260289
0.25837.58529363478714.1938728253212
0.26841.21630338485613.8197231440907
0.27844.71672365491913.6714155161915
0.28848.13908994572613.6892534327638
0.29851.52025847678313.7911755561148
0.3854.87839475419513.8939167232858
0.31858.21369103009113.9312556097117
0.32861.51177916944613.856668707942
0.33864.74854926558913.643338129417
0.34867.89528534795513.2835649923994
0.35870.92342646208212.7890094089179
0.36873.80860851950612.1852798980277
0.37876.5338299074811.5096358121163
0.38879.0916395496410.8117377213923
0.39881.48525684566410.1405841354942
0.4883.7285658554139.54646659373062
0.41885.8449984919239.07317198703499
0.42887.8654164772538.75291077403106
0.43889.8251967852218.60247068096803
0.44891.760806264468.62013411874499
0.45893.7062107635678.78653674082768
0.46895.6894961225619.06310920742021
0.47897.7300776748569.40325664959477
0.48899.8368399933389.75204364388867
0.49902.0074799625810.0558790003853
0.5904.22921973226610.2698888873483
0.51906.4809011963110.3596395822754
0.52908.7362649643310.3081995804954
0.53910.96797507907610.1204368423196
0.54913.1517361003299.81957863574087
0.55915.2697486759279.44697989004616
0.56917.3128370909939.0493972919534
0.57919.280870061038.67266204731013
0.58921.1815115413738.3528671158268
0.59923.0277446455328.10748642527214
0.6924.8348673905847.93827455238671
0.61926.6176839632517.83322630468896
0.62928.3884257731517.77305803472039
0.63930.1556299178177.73795600495148
0.64931.9239047394297.70983828401042
0.65933.6943218948547.67465696875548
0.66935.4651336508097.6223526722409
0.67937.232607958347.54579983474587
0.68938.9919450704647.44374497580331
0.69940.7384020615857.3163402887734
0.7942.4688062522577.17134535044948
0.71944.1835071029527.02282063020681
0.72945.8884984779286.89633125294183
0.73947.5970632634466.82654953914269
0.74949.3300786340786.84875988591181
0.75951.1142935692026.98716297547114
0.76952.9785052752237.24164171973235
0.77954.9484117013547.58308245160527
0.78957.0416004780027.96145405366941
0.79959.2642693823028.3197074866608
0.8961.6107457900188.61030342607291
0.81964.0659346268328.80306287870848
0.82966.6099556580398.89140879778499
0.83969.2238305563088.88829154761668
0.84971.8951955739448.82423166405643
0.85974.6233236402058.74019532787523
0.86977.4228158092588.68711734112475
0.87980.3249544426838.71471694259644
0.88983.3749374444168.85587011832447
0.89986.6222052229249.10796324792339
0.9990.1006413962099.40638119412145
0.91993.7985487134799.60431799762907
0.92997.6306543737159.47734049589985
0.931001.449422166238.8253780793301
0.941005.159525582437.70944871936195
0.951008.993346418566.82809449814211
0.961013.936619940547.82326923279763
0.971022.189269393512.1385011499579
0.981037.1588103172319.7349387268548
0.991060.1646210460730.1985522113981


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
Parameters (R input):
par1 = 0.01 ; par2 = 0.99 ; 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')