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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, 18 Aug 2013 07:18:05 -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/2013/Aug/18/t1376824708btv99qerv0we1ga.htm/, Retrieved Mon, 06 May 2024 07:33:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211167, Retrieved Mon, 06 May 2024 07:33:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsDe Laere Dieter
Estimated Impact124

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Harrell-Davis Quantiles] [Tijdreeks 2 - Stap 7] [2013-08-18 11:18:05] [bc2cf5f41ec5ca561b7a550898b8dd0d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4640
4880
4400
4120
4440
4640
4680
4360
4640
4840
5000
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4720
4840
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4880
4680
4480
4720
5000
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4920
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5320
3960
4440
4360
4840
4880
4880
4400
4800
5280
4720
4440
5200
4240
4520
4640
5040
4840
4760
4520
4680
5480
4680
4160
5360
4200
4520
4600
4880
4840
4600
4520
4600
5760
4640
4520
5400
4200
4600
4480
4680
4400
4480
4840
4680
5480
4680
4440
5280
4240
4600
4640
4920
4560
4400
5080
4640
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4600
4720
5480
4320
4640
4920
4840
4520
4440
5000
4840
5480
4320
4880
5440
4480
4600
4720
5000
4160
4720
5000
4480
5720
4600

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211167&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211167&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211167&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 time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.013891.88754000379145.493147594237
0.024009.81481667581117.502215197365
0.034096.305637624780.2471271301323
0.044149.5614498083455.4617703434106
0.054183.8893977439948.1839091014465
0.064210.5123819600550.1288205434007
0.074234.9701467398354.5258552925008
0.084259.0986652256258.2949994699642
0.094282.9981954695260.0825387304304
0.14306.1385361975359.5046996608461
0.114327.8920666746956.8678527574634
0.124347.7869440906952.8679953425811
0.134365.6017335397648.292034602122
0.144381.3560040734343.8018659401997
0.154395.2433131429939.8362832261965
0.164407.5472568277136.5967233009672
0.174418.5681577250234.0580068547973
0.184428.5739416419132.094491634769
0.194437.7778835791630.5391523707845
0.24446.3389329257729.2599203016545
0.214454.3768949018628.1904921365571
0.224461.9939487807927.3622747255088
0.234469.2947725589226.8672167213983
0.244476.3993574813426.843938176288
0.254483.445324779627.407779273089
0.264490.579832642828.5925677215014
0.274497.9440216729330.3397924918517
0.284505.6544057752432.4882270991111
0.294513.7854799931734.8346022139655
0.34522.3568070455337.1110318679578
0.314531.3268737036939.0532694998553
0.324540.5953625352240.4062888524529
0.334550.0146838982340.9687908791464
0.344559.4100416582640.668752106838
0.354568.6049956214839.5448438093654
0.364577.4473398809337.7671097591055
0.374585.82938581835.6028721843388
0.384593.6981326215233.3242617824537
0.394601.0539420386731.1904711960474
0.44607.9398773321329.3561193825318
0.414614.4262860996427.9017597171045
0.424620.5956036074926.8264403480271
0.434626.5308811350726.0881969310548
0.444632.3092068703825.6511177517419
0.454637.9992056286425.4792471777718
0.464643.6609591580925.5568294384077
0.474649.3470094751125.8420989305716
0.484655.104012534526.3078310042518
0.494660.9753478840926.9340880095525
0.54667.0050803891627.7265748774338
0.514673.2430980374528.7305038714861
0.524679.7503686457230.0211793267475
0.534686.6025239443331.6725356227885
0.544693.8897174669433.7708843326491
0.554701.7110338698936.3541842010027
0.564710.1626346078739.3792516666968
0.574719.3202355437942.7128100825369
0.584729.2182831041646.1197395613604
0.594739.8300040649149.2558243392848
0.64751.0537687501451.7474817706415
0.614762.7111954155353.2302178283869
0.624774.5605844590553.4417122917328
0.634786.3256580755752.2796627685642
0.644797.7350914862949.8549930399029
0.654808.5645272356746.4698861447947
0.664818.6713038085742.5696248044288
0.674828.0139127629438.677898530466
0.684836.6528190964935.2634212986791
0.694844.7350111578932.7006903931969
0.74852.4691141850531.1724585772282
0.714860.0991842724230.7582376876519
0.724867.8829486623231.3997076534675
0.734876.0756950773833.0357725040966
0.744884.9170112657735.554579245557
0.754894.6169508281438.7911440846709
0.764905.3422099213942.5046721919159
0.774917.210055011546.3977569008933
0.784930.3036913804850.2418563862778
0.794944.7216516845454.039371395918
0.84960.6611579361658.210961654471
0.814978.5120224226163.5968624540903
0.824998.9124852549671.29213794692
0.835022.7080399973882.0086339581114
0.845050.7760019986895.4582243104065
0.855083.73705316924110.061691678493
0.865121.64971001205123.241197955571
0.875163.82882999371132.254176475459
0.885208.89723781194135.174825033543
0.895255.06228442692131.593163678671
0.95300.46913037567122.534642007881
0.915343.4349155251109.606445434608
0.925382.5033655500494.0011699469596
0.935416.5535486104676.4276341902338
0.945445.4801349724158.530817496448
0.955471.9296064390345.5828651730326
0.965503.6262695708350.0675371090945
0.975553.0078654861679.8890928758352
0.985627.59021537881111.657201731693
0.995710.8602747209593.710243119187

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 3891.88754000379 & 145.493147594237 \tabularnewline
0.02 & 4009.81481667581 & 117.502215197365 \tabularnewline
0.03 & 4096.3056376247 & 80.2471271301323 \tabularnewline
0.04 & 4149.56144980834 & 55.4617703434106 \tabularnewline
0.05 & 4183.88939774399 & 48.1839091014465 \tabularnewline
0.06 & 4210.51238196005 & 50.1288205434007 \tabularnewline
0.07 & 4234.97014673983 & 54.5258552925008 \tabularnewline
0.08 & 4259.09866522562 & 58.2949994699642 \tabularnewline
0.09 & 4282.99819546952 & 60.0825387304304 \tabularnewline
0.1 & 4306.13853619753 & 59.5046996608461 \tabularnewline
0.11 & 4327.89206667469 & 56.8678527574634 \tabularnewline
0.12 & 4347.78694409069 & 52.8679953425811 \tabularnewline
0.13 & 4365.60173353976 & 48.292034602122 \tabularnewline
0.14 & 4381.35600407343 & 43.8018659401997 \tabularnewline
0.15 & 4395.24331314299 & 39.8362832261965 \tabularnewline
0.16 & 4407.54725682771 & 36.5967233009672 \tabularnewline
0.17 & 4418.56815772502 & 34.0580068547973 \tabularnewline
0.18 & 4428.57394164191 & 32.094491634769 \tabularnewline
0.19 & 4437.77788357916 & 30.5391523707845 \tabularnewline
0.2 & 4446.33893292577 & 29.2599203016545 \tabularnewline
0.21 & 4454.37689490186 & 28.1904921365571 \tabularnewline
0.22 & 4461.99394878079 & 27.3622747255088 \tabularnewline
0.23 & 4469.29477255892 & 26.8672167213983 \tabularnewline
0.24 & 4476.39935748134 & 26.843938176288 \tabularnewline
0.25 & 4483.4453247796 & 27.407779273089 \tabularnewline
0.26 & 4490.5798326428 & 28.5925677215014 \tabularnewline
0.27 & 4497.94402167293 & 30.3397924918517 \tabularnewline
0.28 & 4505.65440577524 & 32.4882270991111 \tabularnewline
0.29 & 4513.78547999317 & 34.8346022139655 \tabularnewline
0.3 & 4522.35680704553 & 37.1110318679578 \tabularnewline
0.31 & 4531.32687370369 & 39.0532694998553 \tabularnewline
0.32 & 4540.59536253522 & 40.4062888524529 \tabularnewline
0.33 & 4550.01468389823 & 40.9687908791464 \tabularnewline
0.34 & 4559.41004165826 & 40.668752106838 \tabularnewline
0.35 & 4568.60499562148 & 39.5448438093654 \tabularnewline
0.36 & 4577.44733988093 & 37.7671097591055 \tabularnewline
0.37 & 4585.829385818 & 35.6028721843388 \tabularnewline
0.38 & 4593.69813262152 & 33.3242617824537 \tabularnewline
0.39 & 4601.05394203867 & 31.1904711960474 \tabularnewline
0.4 & 4607.93987733213 & 29.3561193825318 \tabularnewline
0.41 & 4614.42628609964 & 27.9017597171045 \tabularnewline
0.42 & 4620.59560360749 & 26.8264403480271 \tabularnewline
0.43 & 4626.53088113507 & 26.0881969310548 \tabularnewline
0.44 & 4632.30920687038 & 25.6511177517419 \tabularnewline
0.45 & 4637.99920562864 & 25.4792471777718 \tabularnewline
0.46 & 4643.66095915809 & 25.5568294384077 \tabularnewline
0.47 & 4649.34700947511 & 25.8420989305716 \tabularnewline
0.48 & 4655.1040125345 & 26.3078310042518 \tabularnewline
0.49 & 4660.97534788409 & 26.9340880095525 \tabularnewline
0.5 & 4667.00508038916 & 27.7265748774338 \tabularnewline
0.51 & 4673.24309803745 & 28.7305038714861 \tabularnewline
0.52 & 4679.75036864572 & 30.0211793267475 \tabularnewline
0.53 & 4686.60252394433 & 31.6725356227885 \tabularnewline
0.54 & 4693.88971746694 & 33.7708843326491 \tabularnewline
0.55 & 4701.71103386989 & 36.3541842010027 \tabularnewline
0.56 & 4710.16263460787 & 39.3792516666968 \tabularnewline
0.57 & 4719.32023554379 & 42.7128100825369 \tabularnewline
0.58 & 4729.21828310416 & 46.1197395613604 \tabularnewline
0.59 & 4739.83000406491 & 49.2558243392848 \tabularnewline
0.6 & 4751.05376875014 & 51.7474817706415 \tabularnewline
0.61 & 4762.71119541553 & 53.2302178283869 \tabularnewline
0.62 & 4774.56058445905 & 53.4417122917328 \tabularnewline
0.63 & 4786.32565807557 & 52.2796627685642 \tabularnewline
0.64 & 4797.73509148629 & 49.8549930399029 \tabularnewline
0.65 & 4808.56452723567 & 46.4698861447947 \tabularnewline
0.66 & 4818.67130380857 & 42.5696248044288 \tabularnewline
0.67 & 4828.01391276294 & 38.677898530466 \tabularnewline
0.68 & 4836.65281909649 & 35.2634212986791 \tabularnewline
0.69 & 4844.73501115789 & 32.7006903931969 \tabularnewline
0.7 & 4852.46911418505 & 31.1724585772282 \tabularnewline
0.71 & 4860.09918427242 & 30.7582376876519 \tabularnewline
0.72 & 4867.88294866232 & 31.3997076534675 \tabularnewline
0.73 & 4876.07569507738 & 33.0357725040966 \tabularnewline
0.74 & 4884.91701126577 & 35.554579245557 \tabularnewline
0.75 & 4894.61695082814 & 38.7911440846709 \tabularnewline
0.76 & 4905.34220992139 & 42.5046721919159 \tabularnewline
0.77 & 4917.2100550115 & 46.3977569008933 \tabularnewline
0.78 & 4930.30369138048 & 50.2418563862778 \tabularnewline
0.79 & 4944.72165168454 & 54.039371395918 \tabularnewline
0.8 & 4960.66115793616 & 58.210961654471 \tabularnewline
0.81 & 4978.51202242261 & 63.5968624540903 \tabularnewline
0.82 & 4998.91248525496 & 71.29213794692 \tabularnewline
0.83 & 5022.70803999738 & 82.0086339581114 \tabularnewline
0.84 & 5050.77600199868 & 95.4582243104065 \tabularnewline
0.85 & 5083.73705316924 & 110.061691678493 \tabularnewline
0.86 & 5121.64971001205 & 123.241197955571 \tabularnewline
0.87 & 5163.82882999371 & 132.254176475459 \tabularnewline
0.88 & 5208.89723781194 & 135.174825033543 \tabularnewline
0.89 & 5255.06228442692 & 131.593163678671 \tabularnewline
0.9 & 5300.46913037567 & 122.534642007881 \tabularnewline
0.91 & 5343.4349155251 & 109.606445434608 \tabularnewline
0.92 & 5382.50336555004 & 94.0011699469596 \tabularnewline
0.93 & 5416.55354861046 & 76.4276341902338 \tabularnewline
0.94 & 5445.48013497241 & 58.530817496448 \tabularnewline
0.95 & 5471.92960643903 & 45.5828651730326 \tabularnewline
0.96 & 5503.62626957083 & 50.0675371090945 \tabularnewline
0.97 & 5553.00786548616 & 79.8890928758352 \tabularnewline
0.98 & 5627.59021537881 & 111.657201731693 \tabularnewline
0.99 & 5710.86027472095 & 93.710243119187 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211167&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]3891.88754000379[/C][C]145.493147594237[/C][/ROW]
[ROW][C]0.02[/C][C]4009.81481667581[/C][C]117.502215197365[/C][/ROW]
[ROW][C]0.03[/C][C]4096.3056376247[/C][C]80.2471271301323[/C][/ROW]
[ROW][C]0.04[/C][C]4149.56144980834[/C][C]55.4617703434106[/C][/ROW]
[ROW][C]0.05[/C][C]4183.88939774399[/C][C]48.1839091014465[/C][/ROW]
[ROW][C]0.06[/C][C]4210.51238196005[/C][C]50.1288205434007[/C][/ROW]
[ROW][C]0.07[/C][C]4234.97014673983[/C][C]54.5258552925008[/C][/ROW]
[ROW][C]0.08[/C][C]4259.09866522562[/C][C]58.2949994699642[/C][/ROW]
[ROW][C]0.09[/C][C]4282.99819546952[/C][C]60.0825387304304[/C][/ROW]
[ROW][C]0.1[/C][C]4306.13853619753[/C][C]59.5046996608461[/C][/ROW]
[ROW][C]0.11[/C][C]4327.89206667469[/C][C]56.8678527574634[/C][/ROW]
[ROW][C]0.12[/C][C]4347.78694409069[/C][C]52.8679953425811[/C][/ROW]
[ROW][C]0.13[/C][C]4365.60173353976[/C][C]48.292034602122[/C][/ROW]
[ROW][C]0.14[/C][C]4381.35600407343[/C][C]43.8018659401997[/C][/ROW]
[ROW][C]0.15[/C][C]4395.24331314299[/C][C]39.8362832261965[/C][/ROW]
[ROW][C]0.16[/C][C]4407.54725682771[/C][C]36.5967233009672[/C][/ROW]
[ROW][C]0.17[/C][C]4418.56815772502[/C][C]34.0580068547973[/C][/ROW]
[ROW][C]0.18[/C][C]4428.57394164191[/C][C]32.094491634769[/C][/ROW]
[ROW][C]0.19[/C][C]4437.77788357916[/C][C]30.5391523707845[/C][/ROW]
[ROW][C]0.2[/C][C]4446.33893292577[/C][C]29.2599203016545[/C][/ROW]
[ROW][C]0.21[/C][C]4454.37689490186[/C][C]28.1904921365571[/C][/ROW]
[ROW][C]0.22[/C][C]4461.99394878079[/C][C]27.3622747255088[/C][/ROW]
[ROW][C]0.23[/C][C]4469.29477255892[/C][C]26.8672167213983[/C][/ROW]
[ROW][C]0.24[/C][C]4476.39935748134[/C][C]26.843938176288[/C][/ROW]
[ROW][C]0.25[/C][C]4483.4453247796[/C][C]27.407779273089[/C][/ROW]
[ROW][C]0.26[/C][C]4490.5798326428[/C][C]28.5925677215014[/C][/ROW]
[ROW][C]0.27[/C][C]4497.94402167293[/C][C]30.3397924918517[/C][/ROW]
[ROW][C]0.28[/C][C]4505.65440577524[/C][C]32.4882270991111[/C][/ROW]
[ROW][C]0.29[/C][C]4513.78547999317[/C][C]34.8346022139655[/C][/ROW]
[ROW][C]0.3[/C][C]4522.35680704553[/C][C]37.1110318679578[/C][/ROW]
[ROW][C]0.31[/C][C]4531.32687370369[/C][C]39.0532694998553[/C][/ROW]
[ROW][C]0.32[/C][C]4540.59536253522[/C][C]40.4062888524529[/C][/ROW]
[ROW][C]0.33[/C][C]4550.01468389823[/C][C]40.9687908791464[/C][/ROW]
[ROW][C]0.34[/C][C]4559.41004165826[/C][C]40.668752106838[/C][/ROW]
[ROW][C]0.35[/C][C]4568.60499562148[/C][C]39.5448438093654[/C][/ROW]
[ROW][C]0.36[/C][C]4577.44733988093[/C][C]37.7671097591055[/C][/ROW]
[ROW][C]0.37[/C][C]4585.829385818[/C][C]35.6028721843388[/C][/ROW]
[ROW][C]0.38[/C][C]4593.69813262152[/C][C]33.3242617824537[/C][/ROW]
[ROW][C]0.39[/C][C]4601.05394203867[/C][C]31.1904711960474[/C][/ROW]
[ROW][C]0.4[/C][C]4607.93987733213[/C][C]29.3561193825318[/C][/ROW]
[ROW][C]0.41[/C][C]4614.42628609964[/C][C]27.9017597171045[/C][/ROW]
[ROW][C]0.42[/C][C]4620.59560360749[/C][C]26.8264403480271[/C][/ROW]
[ROW][C]0.43[/C][C]4626.53088113507[/C][C]26.0881969310548[/C][/ROW]
[ROW][C]0.44[/C][C]4632.30920687038[/C][C]25.6511177517419[/C][/ROW]
[ROW][C]0.45[/C][C]4637.99920562864[/C][C]25.4792471777718[/C][/ROW]
[ROW][C]0.46[/C][C]4643.66095915809[/C][C]25.5568294384077[/C][/ROW]
[ROW][C]0.47[/C][C]4649.34700947511[/C][C]25.8420989305716[/C][/ROW]
[ROW][C]0.48[/C][C]4655.1040125345[/C][C]26.3078310042518[/C][/ROW]
[ROW][C]0.49[/C][C]4660.97534788409[/C][C]26.9340880095525[/C][/ROW]
[ROW][C]0.5[/C][C]4667.00508038916[/C][C]27.7265748774338[/C][/ROW]
[ROW][C]0.51[/C][C]4673.24309803745[/C][C]28.7305038714861[/C][/ROW]
[ROW][C]0.52[/C][C]4679.75036864572[/C][C]30.0211793267475[/C][/ROW]
[ROW][C]0.53[/C][C]4686.60252394433[/C][C]31.6725356227885[/C][/ROW]
[ROW][C]0.54[/C][C]4693.88971746694[/C][C]33.7708843326491[/C][/ROW]
[ROW][C]0.55[/C][C]4701.71103386989[/C][C]36.3541842010027[/C][/ROW]
[ROW][C]0.56[/C][C]4710.16263460787[/C][C]39.3792516666968[/C][/ROW]
[ROW][C]0.57[/C][C]4719.32023554379[/C][C]42.7128100825369[/C][/ROW]
[ROW][C]0.58[/C][C]4729.21828310416[/C][C]46.1197395613604[/C][/ROW]
[ROW][C]0.59[/C][C]4739.83000406491[/C][C]49.2558243392848[/C][/ROW]
[ROW][C]0.6[/C][C]4751.05376875014[/C][C]51.7474817706415[/C][/ROW]
[ROW][C]0.61[/C][C]4762.71119541553[/C][C]53.2302178283869[/C][/ROW]
[ROW][C]0.62[/C][C]4774.56058445905[/C][C]53.4417122917328[/C][/ROW]
[ROW][C]0.63[/C][C]4786.32565807557[/C][C]52.2796627685642[/C][/ROW]
[ROW][C]0.64[/C][C]4797.73509148629[/C][C]49.8549930399029[/C][/ROW]
[ROW][C]0.65[/C][C]4808.56452723567[/C][C]46.4698861447947[/C][/ROW]
[ROW][C]0.66[/C][C]4818.67130380857[/C][C]42.5696248044288[/C][/ROW]
[ROW][C]0.67[/C][C]4828.01391276294[/C][C]38.677898530466[/C][/ROW]
[ROW][C]0.68[/C][C]4836.65281909649[/C][C]35.2634212986791[/C][/ROW]
[ROW][C]0.69[/C][C]4844.73501115789[/C][C]32.7006903931969[/C][/ROW]
[ROW][C]0.7[/C][C]4852.46911418505[/C][C]31.1724585772282[/C][/ROW]
[ROW][C]0.71[/C][C]4860.09918427242[/C][C]30.7582376876519[/C][/ROW]
[ROW][C]0.72[/C][C]4867.88294866232[/C][C]31.3997076534675[/C][/ROW]
[ROW][C]0.73[/C][C]4876.07569507738[/C][C]33.0357725040966[/C][/ROW]
[ROW][C]0.74[/C][C]4884.91701126577[/C][C]35.554579245557[/C][/ROW]
[ROW][C]0.75[/C][C]4894.61695082814[/C][C]38.7911440846709[/C][/ROW]
[ROW][C]0.76[/C][C]4905.34220992139[/C][C]42.5046721919159[/C][/ROW]
[ROW][C]0.77[/C][C]4917.2100550115[/C][C]46.3977569008933[/C][/ROW]
[ROW][C]0.78[/C][C]4930.30369138048[/C][C]50.2418563862778[/C][/ROW]
[ROW][C]0.79[/C][C]4944.72165168454[/C][C]54.039371395918[/C][/ROW]
[ROW][C]0.8[/C][C]4960.66115793616[/C][C]58.210961654471[/C][/ROW]
[ROW][C]0.81[/C][C]4978.51202242261[/C][C]63.5968624540903[/C][/ROW]
[ROW][C]0.82[/C][C]4998.91248525496[/C][C]71.29213794692[/C][/ROW]
[ROW][C]0.83[/C][C]5022.70803999738[/C][C]82.0086339581114[/C][/ROW]
[ROW][C]0.84[/C][C]5050.77600199868[/C][C]95.4582243104065[/C][/ROW]
[ROW][C]0.85[/C][C]5083.73705316924[/C][C]110.061691678493[/C][/ROW]
[ROW][C]0.86[/C][C]5121.64971001205[/C][C]123.241197955571[/C][/ROW]
[ROW][C]0.87[/C][C]5163.82882999371[/C][C]132.254176475459[/C][/ROW]
[ROW][C]0.88[/C][C]5208.89723781194[/C][C]135.174825033543[/C][/ROW]
[ROW][C]0.89[/C][C]5255.06228442692[/C][C]131.593163678671[/C][/ROW]
[ROW][C]0.9[/C][C]5300.46913037567[/C][C]122.534642007881[/C][/ROW]
[ROW][C]0.91[/C][C]5343.4349155251[/C][C]109.606445434608[/C][/ROW]
[ROW][C]0.92[/C][C]5382.50336555004[/C][C]94.0011699469596[/C][/ROW]
[ROW][C]0.93[/C][C]5416.55354861046[/C][C]76.4276341902338[/C][/ROW]
[ROW][C]0.94[/C][C]5445.48013497241[/C][C]58.530817496448[/C][/ROW]
[ROW][C]0.95[/C][C]5471.92960643903[/C][C]45.5828651730326[/C][/ROW]
[ROW][C]0.96[/C][C]5503.62626957083[/C][C]50.0675371090945[/C][/ROW]
[ROW][C]0.97[/C][C]5553.00786548616[/C][C]79.8890928758352[/C][/ROW]
[ROW][C]0.98[/C][C]5627.59021537881[/C][C]111.657201731693[/C][/ROW]
[ROW][C]0.99[/C][C]5710.86027472095[/C][C]93.710243119187[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211167&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211167&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
0.013891.88754000379145.493147594237
0.024009.81481667581117.502215197365
0.034096.305637624780.2471271301323
0.044149.5614498083455.4617703434106
0.054183.8893977439948.1839091014465
0.064210.5123819600550.1288205434007
0.074234.9701467398354.5258552925008
0.084259.0986652256258.2949994699642
0.094282.9981954695260.0825387304304
0.14306.1385361975359.5046996608461
0.114327.8920666746956.8678527574634
0.124347.7869440906952.8679953425811
0.134365.6017335397648.292034602122
0.144381.3560040734343.8018659401997
0.154395.2433131429939.8362832261965
0.164407.5472568277136.5967233009672
0.174418.5681577250234.0580068547973
0.184428.5739416419132.094491634769
0.194437.7778835791630.5391523707845
0.24446.3389329257729.2599203016545
0.214454.3768949018628.1904921365571
0.224461.9939487807927.3622747255088
0.234469.2947725589226.8672167213983
0.244476.3993574813426.843938176288
0.254483.445324779627.407779273089
0.264490.579832642828.5925677215014
0.274497.9440216729330.3397924918517
0.284505.6544057752432.4882270991111
0.294513.7854799931734.8346022139655
0.34522.3568070455337.1110318679578
0.314531.3268737036939.0532694998553
0.324540.5953625352240.4062888524529
0.334550.0146838982340.9687908791464
0.344559.4100416582640.668752106838
0.354568.6049956214839.5448438093654
0.364577.4473398809337.7671097591055
0.374585.82938581835.6028721843388
0.384593.6981326215233.3242617824537
0.394601.0539420386731.1904711960474
0.44607.9398773321329.3561193825318
0.414614.4262860996427.9017597171045
0.424620.5956036074926.8264403480271
0.434626.5308811350726.0881969310548
0.444632.3092068703825.6511177517419
0.454637.9992056286425.4792471777718
0.464643.6609591580925.5568294384077
0.474649.3470094751125.8420989305716
0.484655.104012534526.3078310042518
0.494660.9753478840926.9340880095525
0.54667.0050803891627.7265748774338
0.514673.2430980374528.7305038714861
0.524679.7503686457230.0211793267475
0.534686.6025239443331.6725356227885
0.544693.8897174669433.7708843326491
0.554701.7110338698936.3541842010027
0.564710.1626346078739.3792516666968
0.574719.3202355437942.7128100825369
0.584729.2182831041646.1197395613604
0.594739.8300040649149.2558243392848
0.64751.0537687501451.7474817706415
0.614762.7111954155353.2302178283869
0.624774.5605844590553.4417122917328
0.634786.3256580755752.2796627685642
0.644797.7350914862949.8549930399029
0.654808.5645272356746.4698861447947
0.664818.6713038085742.5696248044288
0.674828.0139127629438.677898530466
0.684836.6528190964935.2634212986791
0.694844.7350111578932.7006903931969
0.74852.4691141850531.1724585772282
0.714860.0991842724230.7582376876519
0.724867.8829486623231.3997076534675
0.734876.0756950773833.0357725040966
0.744884.9170112657735.554579245557
0.754894.6169508281438.7911440846709
0.764905.3422099213942.5046721919159
0.774917.210055011546.3977569008933
0.784930.3036913804850.2418563862778
0.794944.7216516845454.039371395918
0.84960.6611579361658.210961654471
0.814978.5120224226163.5968624540903
0.824998.9124852549671.29213794692
0.835022.7080399973882.0086339581114
0.845050.7760019986895.4582243104065
0.855083.73705316924110.061691678493
0.865121.64971001205123.241197955571
0.875163.82882999371132.254176475459
0.885208.89723781194135.174825033543
0.895255.06228442692131.593163678671
0.95300.46913037567122.534642007881
0.915343.4349155251109.606445434608
0.925382.5033655500494.0011699469596
0.935416.5535486104676.4276341902338
0.945445.4801349724158.530817496448
0.955471.9296064390345.5828651730326
0.965503.6262695708350.0675371090945
0.975553.0078654861679.8890928758352
0.985627.59021537881111.657201731693
0.995710.8602747209593.710243119187


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):
par3 <- '0.01'
par2 <- '0.09'
par1 <- '0.01'
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')