FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationMon, 29 Feb 2016 18:05:14 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Feb/29/t1456769150o8nn22bp11t7nod.htm/, Retrieved Tue, 30 Apr 2024 20:25:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=293036, Retrieved Tue, 30 Apr 2024 20:25:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86

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] [] [2016-02-29 17:54:08] [29ab9c45344d5c037bf74b62f65f8e78]
-    D    [Harrell-Davis Quantiles] [Percentielen cons...] [2016-02-29 18:05:14] [0996086de175370e0a22efa864593ca4] [Current]
- R P       [Harrell-Davis Quantiles] [Decielen consumpt...] [2016-02-29 18:06:30] [29ab9c45344d5c037bf74b62f65f8e78]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
91.27
91.51
91.78
91.83
92.01
92.1
92.35
92.46
93.08
93.38
93.46
93.58
93.74
94.18
94.43
94.53
94.66
94.8
95.04
95.29
95.42
95.64
95.82
96.01
96.16
96.4
96.87
97
97.26
97.42
97.64
97.93
98.1
98.29
98.42
98.49
98.67
99.1
99.37
99.54
99.58
99.77
100.06
100.26
100.57
100.94
101.03
101.12
101.26
101.94
102.26
102.51
102.61
102.76
103.04
103.22
103.47
103.64
103.76
103.85

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'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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293036&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293036&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293036&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'Herman Ole Andreas Wold' @ wold.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0191.33576992127050.234372685056234
0.0291.43916635036850.234925759249069
0.0391.55580555658440.235509325090687
0.0491.67020949122170.237196728538078
0.0591.77785559876790.24741334303322
0.0691.88088163420670.272488767691591
0.0791.98381927809610.312471850688078
0.0892.09104732118910.363317173735292
0.0992.20564547512310.41965053564119
0.192.32906202912220.475831258862308
0.1192.46120980013820.526617593081024
0.1292.60078651024650.568079409795935
0.1392.74570691845410.598108404009237
0.1492.89356498980230.616441428623554
0.1593.04205195304060.624880527387989
0.1693.18926708520010.626225774275597
0.1793.33388366894810.623676844964535
0.1893.47516859730640.619972480929146
0.1993.61288806356410.616901215451985
0.293.74715206522730.614972537002075
0.2193.87825227459260.613980440227461
0.2294.00653409189140.613507949985956
0.2394.13232216470880.613063996945646
0.2494.25589786221410.612348507434903
0.2594.37751319308280.611778753456004
0.2694.4974206423740.611720899521831
0.2794.61590108844140.612778885664186
0.2894.73327904859230.615422255190371
0.2994.84992236686770.620004687266504
0.394.96622940543210.626476612281619
0.3195.08260962422230.634948996385102
0.3295.19946331008570.645274648777799
0.3395.31716420799020.657184506565426
0.3495.43604624061570.670550787207492
0.3595.5563934703790.684969910788681
0.3695.67843154335160.700328082465793
0.3795.80231909870970.716258828848833
0.3895.92813866774410.732367785184562
0.3996.0558878759350.747917156221017
0.496.1854727823760.762285107871809
0.4196.31670560483270.774978524754057
0.4296.44930879013640.78526741827314
0.4396.58292652450340.792786107144055
0.4496.7171436061620.797135755929843
0.4596.85151043328340.798035564414658
0.4696.9855719501830.795775788280151
0.4797.11889788711680.790616038941243
0.4897.25111153885120.782823763459942
0.4997.38191457004940.773158181007501
0.597.51110578288840.762334744132897
0.5197.63859232151110.750705574789273
0.5297.76439236348980.73947059587027
0.5397.88862896984020.72911024242304
0.5498.01151547852490.720050706104813
0.5598.13333366284860.712883649864153
0.5698.25440679818440.707727425790232
0.5798.37507065242370.704704582686968
0.5898.49564601607290.703327905613235
0.5998.61641646871030.70339127582298
0.698.73761445482160.704260061888999
0.6198.85941738619080.705440992802497
0.6298.98195358970310.706663392953522
0.6399.10531588218030.707536958533376
0.6499.22957891473460.708114919779664
0.6599.35481571213350.708588461896234
0.6699.48110937280050.70904275474802
0.6799.60855768542430.709768802260567
0.6899.73727103655290.7109297924072
0.6999.86736664107980.712360842712655
0.799.99896385159850.713984389856384
0.71100.1321852290040.715642949199086
0.72100.2671657634190.717031224581673
0.73100.4040684184930.718323468119022
0.74100.5430991574950.719681455494259
0.75100.6845105943550.721574962380934
0.76100.8285824168590.724470778623433
0.77100.9755703022850.728487696978709
0.78101.1256235054580.733251085647831
0.79101.2786831701320.737744125308937
0.8101.4343853715520.739790411592099
0.81101.592000430890.737260549199911
0.82101.7504388430950.727882995925264
0.83101.908341911980.709930894000174
0.84102.0642531256490.683083720641554
0.85102.2168397815830.648402667715673
0.86102.3651118218650.608324053689875
0.87102.508575144690.566100223057699
0.88102.6472656461070.525060195514244
0.89102.7816378149340.487660470149745
0.9102.9123211405620.45460549490698
0.91103.0397978353160.42479762003086
0.92103.1640852883120.395681368844434
0.93103.2845184155260.36407572696414
0.94103.399714225060.327286476527438
0.95103.507748764730.283908565656248
0.96103.606454576480.234639069070377
0.97103.6935468567970.182741727950491
0.98103.7661792186070.13492409877665
0.99103.8200637495950.101517784544752

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 91.3357699212705 & 0.234372685056234 \tabularnewline
0.02 & 91.4391663503685 & 0.234925759249069 \tabularnewline
0.03 & 91.5558055565844 & 0.235509325090687 \tabularnewline
0.04 & 91.6702094912217 & 0.237196728538078 \tabularnewline
0.05 & 91.7778555987679 & 0.24741334303322 \tabularnewline
0.06 & 91.8808816342067 & 0.272488767691591 \tabularnewline
0.07 & 91.9838192780961 & 0.312471850688078 \tabularnewline
0.08 & 92.0910473211891 & 0.363317173735292 \tabularnewline
0.09 & 92.2056454751231 & 0.41965053564119 \tabularnewline
0.1 & 92.3290620291222 & 0.475831258862308 \tabularnewline
0.11 & 92.4612098001382 & 0.526617593081024 \tabularnewline
0.12 & 92.6007865102465 & 0.568079409795935 \tabularnewline
0.13 & 92.7457069184541 & 0.598108404009237 \tabularnewline
0.14 & 92.8935649898023 & 0.616441428623554 \tabularnewline
0.15 & 93.0420519530406 & 0.624880527387989 \tabularnewline
0.16 & 93.1892670852001 & 0.626225774275597 \tabularnewline
0.17 & 93.3338836689481 & 0.623676844964535 \tabularnewline
0.18 & 93.4751685973064 & 0.619972480929146 \tabularnewline
0.19 & 93.6128880635641 & 0.616901215451985 \tabularnewline
0.2 & 93.7471520652273 & 0.614972537002075 \tabularnewline
0.21 & 93.8782522745926 & 0.613980440227461 \tabularnewline
0.22 & 94.0065340918914 & 0.613507949985956 \tabularnewline
0.23 & 94.1323221647088 & 0.613063996945646 \tabularnewline
0.24 & 94.2558978622141 & 0.612348507434903 \tabularnewline
0.25 & 94.3775131930828 & 0.611778753456004 \tabularnewline
0.26 & 94.497420642374 & 0.611720899521831 \tabularnewline
0.27 & 94.6159010884414 & 0.612778885664186 \tabularnewline
0.28 & 94.7332790485923 & 0.615422255190371 \tabularnewline
0.29 & 94.8499223668677 & 0.620004687266504 \tabularnewline
0.3 & 94.9662294054321 & 0.626476612281619 \tabularnewline
0.31 & 95.0826096242223 & 0.634948996385102 \tabularnewline
0.32 & 95.1994633100857 & 0.645274648777799 \tabularnewline
0.33 & 95.3171642079902 & 0.657184506565426 \tabularnewline
0.34 & 95.4360462406157 & 0.670550787207492 \tabularnewline
0.35 & 95.556393470379 & 0.684969910788681 \tabularnewline
0.36 & 95.6784315433516 & 0.700328082465793 \tabularnewline
0.37 & 95.8023190987097 & 0.716258828848833 \tabularnewline
0.38 & 95.9281386677441 & 0.732367785184562 \tabularnewline
0.39 & 96.055887875935 & 0.747917156221017 \tabularnewline
0.4 & 96.185472782376 & 0.762285107871809 \tabularnewline
0.41 & 96.3167056048327 & 0.774978524754057 \tabularnewline
0.42 & 96.4493087901364 & 0.78526741827314 \tabularnewline
0.43 & 96.5829265245034 & 0.792786107144055 \tabularnewline
0.44 & 96.717143606162 & 0.797135755929843 \tabularnewline
0.45 & 96.8515104332834 & 0.798035564414658 \tabularnewline
0.46 & 96.985571950183 & 0.795775788280151 \tabularnewline
0.47 & 97.1188978871168 & 0.790616038941243 \tabularnewline
0.48 & 97.2511115388512 & 0.782823763459942 \tabularnewline
0.49 & 97.3819145700494 & 0.773158181007501 \tabularnewline
0.5 & 97.5111057828884 & 0.762334744132897 \tabularnewline
0.51 & 97.6385923215111 & 0.750705574789273 \tabularnewline
0.52 & 97.7643923634898 & 0.73947059587027 \tabularnewline
0.53 & 97.8886289698402 & 0.72911024242304 \tabularnewline
0.54 & 98.0115154785249 & 0.720050706104813 \tabularnewline
0.55 & 98.1333336628486 & 0.712883649864153 \tabularnewline
0.56 & 98.2544067981844 & 0.707727425790232 \tabularnewline
0.57 & 98.3750706524237 & 0.704704582686968 \tabularnewline
0.58 & 98.4956460160729 & 0.703327905613235 \tabularnewline
0.59 & 98.6164164687103 & 0.70339127582298 \tabularnewline
0.6 & 98.7376144548216 & 0.704260061888999 \tabularnewline
0.61 & 98.8594173861908 & 0.705440992802497 \tabularnewline
0.62 & 98.9819535897031 & 0.706663392953522 \tabularnewline
0.63 & 99.1053158821803 & 0.707536958533376 \tabularnewline
0.64 & 99.2295789147346 & 0.708114919779664 \tabularnewline
0.65 & 99.3548157121335 & 0.708588461896234 \tabularnewline
0.66 & 99.4811093728005 & 0.70904275474802 \tabularnewline
0.67 & 99.6085576854243 & 0.709768802260567 \tabularnewline
0.68 & 99.7372710365529 & 0.7109297924072 \tabularnewline
0.69 & 99.8673666410798 & 0.712360842712655 \tabularnewline
0.7 & 99.9989638515985 & 0.713984389856384 \tabularnewline
0.71 & 100.132185229004 & 0.715642949199086 \tabularnewline
0.72 & 100.267165763419 & 0.717031224581673 \tabularnewline
0.73 & 100.404068418493 & 0.718323468119022 \tabularnewline
0.74 & 100.543099157495 & 0.719681455494259 \tabularnewline
0.75 & 100.684510594355 & 0.721574962380934 \tabularnewline
0.76 & 100.828582416859 & 0.724470778623433 \tabularnewline
0.77 & 100.975570302285 & 0.728487696978709 \tabularnewline
0.78 & 101.125623505458 & 0.733251085647831 \tabularnewline
0.79 & 101.278683170132 & 0.737744125308937 \tabularnewline
0.8 & 101.434385371552 & 0.739790411592099 \tabularnewline
0.81 & 101.59200043089 & 0.737260549199911 \tabularnewline
0.82 & 101.750438843095 & 0.727882995925264 \tabularnewline
0.83 & 101.90834191198 & 0.709930894000174 \tabularnewline
0.84 & 102.064253125649 & 0.683083720641554 \tabularnewline
0.85 & 102.216839781583 & 0.648402667715673 \tabularnewline
0.86 & 102.365111821865 & 0.608324053689875 \tabularnewline
0.87 & 102.50857514469 & 0.566100223057699 \tabularnewline
0.88 & 102.647265646107 & 0.525060195514244 \tabularnewline
0.89 & 102.781637814934 & 0.487660470149745 \tabularnewline
0.9 & 102.912321140562 & 0.45460549490698 \tabularnewline
0.91 & 103.039797835316 & 0.42479762003086 \tabularnewline
0.92 & 103.164085288312 & 0.395681368844434 \tabularnewline
0.93 & 103.284518415526 & 0.36407572696414 \tabularnewline
0.94 & 103.39971422506 & 0.327286476527438 \tabularnewline
0.95 & 103.50774876473 & 0.283908565656248 \tabularnewline
0.96 & 103.60645457648 & 0.234639069070377 \tabularnewline
0.97 & 103.693546856797 & 0.182741727950491 \tabularnewline
0.98 & 103.766179218607 & 0.13492409877665 \tabularnewline
0.99 & 103.820063749595 & 0.101517784544752 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=293036&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]91.3357699212705[/C][C]0.234372685056234[/C][/ROW]
[ROW][C]0.02[/C][C]91.4391663503685[/C][C]0.234925759249069[/C][/ROW]
[ROW][C]0.03[/C][C]91.5558055565844[/C][C]0.235509325090687[/C][/ROW]
[ROW][C]0.04[/C][C]91.6702094912217[/C][C]0.237196728538078[/C][/ROW]
[ROW][C]0.05[/C][C]91.7778555987679[/C][C]0.24741334303322[/C][/ROW]
[ROW][C]0.06[/C][C]91.8808816342067[/C][C]0.272488767691591[/C][/ROW]
[ROW][C]0.07[/C][C]91.9838192780961[/C][C]0.312471850688078[/C][/ROW]
[ROW][C]0.08[/C][C]92.0910473211891[/C][C]0.363317173735292[/C][/ROW]
[ROW][C]0.09[/C][C]92.2056454751231[/C][C]0.41965053564119[/C][/ROW]
[ROW][C]0.1[/C][C]92.3290620291222[/C][C]0.475831258862308[/C][/ROW]
[ROW][C]0.11[/C][C]92.4612098001382[/C][C]0.526617593081024[/C][/ROW]
[ROW][C]0.12[/C][C]92.6007865102465[/C][C]0.568079409795935[/C][/ROW]
[ROW][C]0.13[/C][C]92.7457069184541[/C][C]0.598108404009237[/C][/ROW]
[ROW][C]0.14[/C][C]92.8935649898023[/C][C]0.616441428623554[/C][/ROW]
[ROW][C]0.15[/C][C]93.0420519530406[/C][C]0.624880527387989[/C][/ROW]
[ROW][C]0.16[/C][C]93.1892670852001[/C][C]0.626225774275597[/C][/ROW]
[ROW][C]0.17[/C][C]93.3338836689481[/C][C]0.623676844964535[/C][/ROW]
[ROW][C]0.18[/C][C]93.4751685973064[/C][C]0.619972480929146[/C][/ROW]
[ROW][C]0.19[/C][C]93.6128880635641[/C][C]0.616901215451985[/C][/ROW]
[ROW][C]0.2[/C][C]93.7471520652273[/C][C]0.614972537002075[/C][/ROW]
[ROW][C]0.21[/C][C]93.8782522745926[/C][C]0.613980440227461[/C][/ROW]
[ROW][C]0.22[/C][C]94.0065340918914[/C][C]0.613507949985956[/C][/ROW]
[ROW][C]0.23[/C][C]94.1323221647088[/C][C]0.613063996945646[/C][/ROW]
[ROW][C]0.24[/C][C]94.2558978622141[/C][C]0.612348507434903[/C][/ROW]
[ROW][C]0.25[/C][C]94.3775131930828[/C][C]0.611778753456004[/C][/ROW]
[ROW][C]0.26[/C][C]94.497420642374[/C][C]0.611720899521831[/C][/ROW]
[ROW][C]0.27[/C][C]94.6159010884414[/C][C]0.612778885664186[/C][/ROW]
[ROW][C]0.28[/C][C]94.7332790485923[/C][C]0.615422255190371[/C][/ROW]
[ROW][C]0.29[/C][C]94.8499223668677[/C][C]0.620004687266504[/C][/ROW]
[ROW][C]0.3[/C][C]94.9662294054321[/C][C]0.626476612281619[/C][/ROW]
[ROW][C]0.31[/C][C]95.0826096242223[/C][C]0.634948996385102[/C][/ROW]
[ROW][C]0.32[/C][C]95.1994633100857[/C][C]0.645274648777799[/C][/ROW]
[ROW][C]0.33[/C][C]95.3171642079902[/C][C]0.657184506565426[/C][/ROW]
[ROW][C]0.34[/C][C]95.4360462406157[/C][C]0.670550787207492[/C][/ROW]
[ROW][C]0.35[/C][C]95.556393470379[/C][C]0.684969910788681[/C][/ROW]
[ROW][C]0.36[/C][C]95.6784315433516[/C][C]0.700328082465793[/C][/ROW]
[ROW][C]0.37[/C][C]95.8023190987097[/C][C]0.716258828848833[/C][/ROW]
[ROW][C]0.38[/C][C]95.9281386677441[/C][C]0.732367785184562[/C][/ROW]
[ROW][C]0.39[/C][C]96.055887875935[/C][C]0.747917156221017[/C][/ROW]
[ROW][C]0.4[/C][C]96.185472782376[/C][C]0.762285107871809[/C][/ROW]
[ROW][C]0.41[/C][C]96.3167056048327[/C][C]0.774978524754057[/C][/ROW]
[ROW][C]0.42[/C][C]96.4493087901364[/C][C]0.78526741827314[/C][/ROW]
[ROW][C]0.43[/C][C]96.5829265245034[/C][C]0.792786107144055[/C][/ROW]
[ROW][C]0.44[/C][C]96.717143606162[/C][C]0.797135755929843[/C][/ROW]
[ROW][C]0.45[/C][C]96.8515104332834[/C][C]0.798035564414658[/C][/ROW]
[ROW][C]0.46[/C][C]96.985571950183[/C][C]0.795775788280151[/C][/ROW]
[ROW][C]0.47[/C][C]97.1188978871168[/C][C]0.790616038941243[/C][/ROW]
[ROW][C]0.48[/C][C]97.2511115388512[/C][C]0.782823763459942[/C][/ROW]
[ROW][C]0.49[/C][C]97.3819145700494[/C][C]0.773158181007501[/C][/ROW]
[ROW][C]0.5[/C][C]97.5111057828884[/C][C]0.762334744132897[/C][/ROW]
[ROW][C]0.51[/C][C]97.6385923215111[/C][C]0.750705574789273[/C][/ROW]
[ROW][C]0.52[/C][C]97.7643923634898[/C][C]0.73947059587027[/C][/ROW]
[ROW][C]0.53[/C][C]97.8886289698402[/C][C]0.72911024242304[/C][/ROW]
[ROW][C]0.54[/C][C]98.0115154785249[/C][C]0.720050706104813[/C][/ROW]
[ROW][C]0.55[/C][C]98.1333336628486[/C][C]0.712883649864153[/C][/ROW]
[ROW][C]0.56[/C][C]98.2544067981844[/C][C]0.707727425790232[/C][/ROW]
[ROW][C]0.57[/C][C]98.3750706524237[/C][C]0.704704582686968[/C][/ROW]
[ROW][C]0.58[/C][C]98.4956460160729[/C][C]0.703327905613235[/C][/ROW]
[ROW][C]0.59[/C][C]98.6164164687103[/C][C]0.70339127582298[/C][/ROW]
[ROW][C]0.6[/C][C]98.7376144548216[/C][C]0.704260061888999[/C][/ROW]
[ROW][C]0.61[/C][C]98.8594173861908[/C][C]0.705440992802497[/C][/ROW]
[ROW][C]0.62[/C][C]98.9819535897031[/C][C]0.706663392953522[/C][/ROW]
[ROW][C]0.63[/C][C]99.1053158821803[/C][C]0.707536958533376[/C][/ROW]
[ROW][C]0.64[/C][C]99.2295789147346[/C][C]0.708114919779664[/C][/ROW]
[ROW][C]0.65[/C][C]99.3548157121335[/C][C]0.708588461896234[/C][/ROW]
[ROW][C]0.66[/C][C]99.4811093728005[/C][C]0.70904275474802[/C][/ROW]
[ROW][C]0.67[/C][C]99.6085576854243[/C][C]0.709768802260567[/C][/ROW]
[ROW][C]0.68[/C][C]99.7372710365529[/C][C]0.7109297924072[/C][/ROW]
[ROW][C]0.69[/C][C]99.8673666410798[/C][C]0.712360842712655[/C][/ROW]
[ROW][C]0.7[/C][C]99.9989638515985[/C][C]0.713984389856384[/C][/ROW]
[ROW][C]0.71[/C][C]100.132185229004[/C][C]0.715642949199086[/C][/ROW]
[ROW][C]0.72[/C][C]100.267165763419[/C][C]0.717031224581673[/C][/ROW]
[ROW][C]0.73[/C][C]100.404068418493[/C][C]0.718323468119022[/C][/ROW]
[ROW][C]0.74[/C][C]100.543099157495[/C][C]0.719681455494259[/C][/ROW]
[ROW][C]0.75[/C][C]100.684510594355[/C][C]0.721574962380934[/C][/ROW]
[ROW][C]0.76[/C][C]100.828582416859[/C][C]0.724470778623433[/C][/ROW]
[ROW][C]0.77[/C][C]100.975570302285[/C][C]0.728487696978709[/C][/ROW]
[ROW][C]0.78[/C][C]101.125623505458[/C][C]0.733251085647831[/C][/ROW]
[ROW][C]0.79[/C][C]101.278683170132[/C][C]0.737744125308937[/C][/ROW]
[ROW][C]0.8[/C][C]101.434385371552[/C][C]0.739790411592099[/C][/ROW]
[ROW][C]0.81[/C][C]101.59200043089[/C][C]0.737260549199911[/C][/ROW]
[ROW][C]0.82[/C][C]101.750438843095[/C][C]0.727882995925264[/C][/ROW]
[ROW][C]0.83[/C][C]101.90834191198[/C][C]0.709930894000174[/C][/ROW]
[ROW][C]0.84[/C][C]102.064253125649[/C][C]0.683083720641554[/C][/ROW]
[ROW][C]0.85[/C][C]102.216839781583[/C][C]0.648402667715673[/C][/ROW]
[ROW][C]0.86[/C][C]102.365111821865[/C][C]0.608324053689875[/C][/ROW]
[ROW][C]0.87[/C][C]102.50857514469[/C][C]0.566100223057699[/C][/ROW]
[ROW][C]0.88[/C][C]102.647265646107[/C][C]0.525060195514244[/C][/ROW]
[ROW][C]0.89[/C][C]102.781637814934[/C][C]0.487660470149745[/C][/ROW]
[ROW][C]0.9[/C][C]102.912321140562[/C][C]0.45460549490698[/C][/ROW]
[ROW][C]0.91[/C][C]103.039797835316[/C][C]0.42479762003086[/C][/ROW]
[ROW][C]0.92[/C][C]103.164085288312[/C][C]0.395681368844434[/C][/ROW]
[ROW][C]0.93[/C][C]103.284518415526[/C][C]0.36407572696414[/C][/ROW]
[ROW][C]0.94[/C][C]103.39971422506[/C][C]0.327286476527438[/C][/ROW]
[ROW][C]0.95[/C][C]103.50774876473[/C][C]0.283908565656248[/C][/ROW]
[ROW][C]0.96[/C][C]103.60645457648[/C][C]0.234639069070377[/C][/ROW]
[ROW][C]0.97[/C][C]103.693546856797[/C][C]0.182741727950491[/C][/ROW]
[ROW][C]0.98[/C][C]103.766179218607[/C][C]0.13492409877665[/C][/ROW]
[ROW][C]0.99[/C][C]103.820063749595[/C][C]0.101517784544752[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=293036&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=293036&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
0.0191.33576992127050.234372685056234
0.0291.43916635036850.234925759249069
0.0391.55580555658440.235509325090687
0.0491.67020949122170.237196728538078
0.0591.77785559876790.24741334303322
0.0691.88088163420670.272488767691591
0.0791.98381927809610.312471850688078
0.0892.09104732118910.363317173735292
0.0992.20564547512310.41965053564119
0.192.32906202912220.475831258862308
0.1192.46120980013820.526617593081024
0.1292.60078651024650.568079409795935
0.1392.74570691845410.598108404009237
0.1492.89356498980230.616441428623554
0.1593.04205195304060.624880527387989
0.1693.18926708520010.626225774275597
0.1793.33388366894810.623676844964535
0.1893.47516859730640.619972480929146
0.1993.61288806356410.616901215451985
0.293.74715206522730.614972537002075
0.2193.87825227459260.613980440227461
0.2294.00653409189140.613507949985956
0.2394.13232216470880.613063996945646
0.2494.25589786221410.612348507434903
0.2594.37751319308280.611778753456004
0.2694.4974206423740.611720899521831
0.2794.61590108844140.612778885664186
0.2894.73327904859230.615422255190371
0.2994.84992236686770.620004687266504
0.394.96622940543210.626476612281619
0.3195.08260962422230.634948996385102
0.3295.19946331008570.645274648777799
0.3395.31716420799020.657184506565426
0.3495.43604624061570.670550787207492
0.3595.5563934703790.684969910788681
0.3695.67843154335160.700328082465793
0.3795.80231909870970.716258828848833
0.3895.92813866774410.732367785184562
0.3996.0558878759350.747917156221017
0.496.1854727823760.762285107871809
0.4196.31670560483270.774978524754057
0.4296.44930879013640.78526741827314
0.4396.58292652450340.792786107144055
0.4496.7171436061620.797135755929843
0.4596.85151043328340.798035564414658
0.4696.9855719501830.795775788280151
0.4797.11889788711680.790616038941243
0.4897.25111153885120.782823763459942
0.4997.38191457004940.773158181007501
0.597.51110578288840.762334744132897
0.5197.63859232151110.750705574789273
0.5297.76439236348980.73947059587027
0.5397.88862896984020.72911024242304
0.5498.01151547852490.720050706104813
0.5598.13333366284860.712883649864153
0.5698.25440679818440.707727425790232
0.5798.37507065242370.704704582686968
0.5898.49564601607290.703327905613235
0.5998.61641646871030.70339127582298
0.698.73761445482160.704260061888999
0.6198.85941738619080.705440992802497
0.6298.98195358970310.706663392953522
0.6399.10531588218030.707536958533376
0.6499.22957891473460.708114919779664
0.6599.35481571213350.708588461896234
0.6699.48110937280050.70904275474802
0.6799.60855768542430.709768802260567
0.6899.73727103655290.7109297924072
0.6999.86736664107980.712360842712655
0.799.99896385159850.713984389856384
0.71100.1321852290040.715642949199086
0.72100.2671657634190.717031224581673
0.73100.4040684184930.718323468119022
0.74100.5430991574950.719681455494259
0.75100.6845105943550.721574962380934
0.76100.8285824168590.724470778623433
0.77100.9755703022850.728487696978709
0.78101.1256235054580.733251085647831
0.79101.2786831701320.737744125308937
0.8101.4343853715520.739790411592099
0.81101.592000430890.737260549199911
0.82101.7504388430950.727882995925264
0.83101.908341911980.709930894000174
0.84102.0642531256490.683083720641554
0.85102.2168397815830.648402667715673
0.86102.3651118218650.608324053689875
0.87102.508575144690.566100223057699
0.88102.6472656461070.525060195514244
0.89102.7816378149340.487660470149745
0.9102.9123211405620.45460549490698
0.91103.0397978353160.42479762003086
0.92103.1640852883120.395681368844434
0.93103.2845184155260.36407572696414
0.94103.399714225060.327286476527438
0.95103.507748764730.283908565656248
0.96103.606454576480.234639069070377
0.97103.6935468567970.182741727950491
0.98103.7661792186070.13492409877665
0.99103.8200637495950.101517784544752


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')