FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_harrell_davies.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationMon, 27 Oct 2008 16:48:24 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/28/t1225149102sm5te0pbvav7a81.htm/, Retrieved Sun, 19 May 2024 18:04:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19709, Retrieved Sun, 19 May 2024 18:04:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact183

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Harrell-Davis Quantiles] [Investigating dis...] [2007-10-22 20:06:26] [b9964c45117f7aac638ab9056d451faa]
F   PD  [Harrell-Davis Quantiles] [Harrell - Davis Q...] [2008-10-27 22:09:25] [b591abfa820a394aeb0c5ebd9cfa1091]
-    D      [Harrell-Davis Quantiles] [Harrell-Davis Qua...] [2008-10-27 22:48:24] [6d5cd2fe15d123a10639b4bf141c23b5] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13812
13031
12574
11964
11451
11346
11353
10702
10646
10556
10463
10407
10625
10872
10805
10653
10574
10431
10383
10296
10872
10635
10297
10570
10662
10709
10413
10846
10371
9924
9828
9897
9721
10171
10738
10812
10511
10244
10368
10457
10186
10166
10827
10997
10940
10756
10893
10236
9960
10018
10063
10002
9728
10002
10177
9948
9394
9308
9155
9103
9732

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19709&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19709&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19709&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Harrell-Davis Quantiles
quantilesvaluestandard error
0.019126.3351765427674.94861192908
0.029170.82205991521115.920323329112
0.039232.14064811326157.039100575474
0.049304.35255830025188.553533423985
0.059381.66050287053206.758564674422
0.069459.01046713178210.907174737959
0.079532.42166218904202.734149136962
0.089599.23532040266186.277355698808
0.099658.18119437576166.501867367863
0.19709.19232769118147.621769521320
0.119753.0265811136131.989476811480
0.129790.83517698197119.973491588369
0.139823.81196174717110.767462716204
0.149852.99082853378103.355972107700
0.159879.1851841008597.1040869691877
0.169903.0189661206791.8724104147151
0.179924.99099054687.811835308924
0.189945.530876772385.1763784674898
0.199965.0283171032384.0843326257743
0.29983.836173640684.4603743563675
0.2110002.257589064986.0099116793167
0.2210020.529134746488.302125542407
0.2310038.809205766390.8568548251492
0.2410057.176421186093.271396491626
0.2510075.638629279895.1802379033552
0.2610094.150135988896.428778220377
0.2710112.633180476496.9574226952634
0.2810130.999347473296.8287995022713
0.2910149.167259227796.2264618002136
0.310167.074189120195.327336384555
0.3110184.680811768094.3130411852809
0.3210201.969789918293.3080821256555
0.3310218.940003867892.3603456191593
0.3410235.598781299391.504620601875
0.3510251.954454691890.6403233505702
0.3610268.011061387489.7083842506736
0.3710283.766196688488.6245966981783
0.3810299.212150670387.3553197333422
0.3910314.339697078085.8902654134722
0.410329.143388490284.2880841937152
0.4110343.627001466482.6363270789638
0.4210357.807855426481.0680051710638
0.4310371.719036577079.7131822732307
0.4410385.409003933078.701127775062
0.4510398.938544009978.1107561069595
0.4610412.375490580577.9776246011486
0.4710425.787972929978.3058569226583
0.4810439.237161772178.9781869961458
0.4910452.770532560979.8882290594606
0.510466.416569651980.9078306398646
0.5110480.181617886881.8426078414282
0.5210494.049289477882.5403504371034
0.5310507.982498744982.8662895731932
0.5410521.927870571682.7450192034388
0.5510535.821989901582.1282332146602
0.5610549.598758492781.0141687108166
0.5710563.197018111979.4807838318167
0.5810576.567590216277.6157811628815
0.5910589.678963851575.538675849603
0.610602.521021055173.4267962325614
0.6110615.106403070671.4274562165892
0.6210627.469369869369.6864134052786
0.6310639.662268319668.3074204349445
0.6410651.749979827767.3789623546221
0.6510663.802946293666.8898729693741
0.6610675.889555418666.8331550273454
0.6710688.068787707867.0890241214549
0.6810700.384078563667.5483093978224
0.6910712.859328468468.0623186653952
0.710725.497910994268.4735235768593
0.7110738.285399809368.6699599887703
0.7210751.196583419168.561699686136
0.7310764.207174708668.1387615949756
0.7410777.310442786167.474527432503
0.7510790.538747160266.7333214474643
0.7610803.989537823066.246981737926
0.7710817.854663813766.4730122422181
0.7810832.450701975968.046981770117
0.7910848.246529094571.7511891825314
0.810865.88289929778.4486315046414
0.8110886.178222770788.9196992765297
0.8210910.1164012065103.677304917904
0.8310938.817853295122.842699893775
0.8410973.5042840254146.118621864564
0.8511015.4795783754172.867084670357
0.8611066.1581444177202.351240901872
0.8711127.1692201087234.218620470374
0.8811200.5414046781269.006363834173
0.8911288.9221439979308.517349014425
0.911395.7239237972355.415705690934
0.9111525.0486879504411.695128236957
0.9211681.2827772838476.383051995396
0.9311868.4255977195543.70103044219
0.9412089.4693032222603.309561188664
0.9512346.1900464509643.682697680812
0.9612638.9211820313658.989451694093
0.9712963.8136834444658.38618071229
0.9813303.4218520790669.471985897264
0.9913611.5264922187714.373198642714

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 9126.33517654276 & 74.94861192908 \tabularnewline
0.02 & 9170.82205991521 & 115.920323329112 \tabularnewline
0.03 & 9232.14064811326 & 157.039100575474 \tabularnewline
0.04 & 9304.35255830025 & 188.553533423985 \tabularnewline
0.05 & 9381.66050287053 & 206.758564674422 \tabularnewline
0.06 & 9459.01046713178 & 210.907174737959 \tabularnewline
0.07 & 9532.42166218904 & 202.734149136962 \tabularnewline
0.08 & 9599.23532040266 & 186.277355698808 \tabularnewline
0.09 & 9658.18119437576 & 166.501867367863 \tabularnewline
0.1 & 9709.19232769118 & 147.621769521320 \tabularnewline
0.11 & 9753.0265811136 & 131.989476811480 \tabularnewline
0.12 & 9790.83517698197 & 119.973491588369 \tabularnewline
0.13 & 9823.81196174717 & 110.767462716204 \tabularnewline
0.14 & 9852.99082853378 & 103.355972107700 \tabularnewline
0.15 & 9879.18518410085 & 97.1040869691877 \tabularnewline
0.16 & 9903.01896612067 & 91.8724104147151 \tabularnewline
0.17 & 9924.990990546 & 87.811835308924 \tabularnewline
0.18 & 9945.5308767723 & 85.1763784674898 \tabularnewline
0.19 & 9965.02831710323 & 84.0843326257743 \tabularnewline
0.2 & 9983.8361736406 & 84.4603743563675 \tabularnewline
0.21 & 10002.2575890649 & 86.0099116793167 \tabularnewline
0.22 & 10020.5291347464 & 88.302125542407 \tabularnewline
0.23 & 10038.8092057663 & 90.8568548251492 \tabularnewline
0.24 & 10057.1764211860 & 93.271396491626 \tabularnewline
0.25 & 10075.6386292798 & 95.1802379033552 \tabularnewline
0.26 & 10094.1501359888 & 96.428778220377 \tabularnewline
0.27 & 10112.6331804764 & 96.9574226952634 \tabularnewline
0.28 & 10130.9993474732 & 96.8287995022713 \tabularnewline
0.29 & 10149.1672592277 & 96.2264618002136 \tabularnewline
0.3 & 10167.0741891201 & 95.327336384555 \tabularnewline
0.31 & 10184.6808117680 & 94.3130411852809 \tabularnewline
0.32 & 10201.9697899182 & 93.3080821256555 \tabularnewline
0.33 & 10218.9400038678 & 92.3603456191593 \tabularnewline
0.34 & 10235.5987812993 & 91.504620601875 \tabularnewline
0.35 & 10251.9544546918 & 90.6403233505702 \tabularnewline
0.36 & 10268.0110613874 & 89.7083842506736 \tabularnewline
0.37 & 10283.7661966884 & 88.6245966981783 \tabularnewline
0.38 & 10299.2121506703 & 87.3553197333422 \tabularnewline
0.39 & 10314.3396970780 & 85.8902654134722 \tabularnewline
0.4 & 10329.1433884902 & 84.2880841937152 \tabularnewline
0.41 & 10343.6270014664 & 82.6363270789638 \tabularnewline
0.42 & 10357.8078554264 & 81.0680051710638 \tabularnewline
0.43 & 10371.7190365770 & 79.7131822732307 \tabularnewline
0.44 & 10385.4090039330 & 78.701127775062 \tabularnewline
0.45 & 10398.9385440099 & 78.1107561069595 \tabularnewline
0.46 & 10412.3754905805 & 77.9776246011486 \tabularnewline
0.47 & 10425.7879729299 & 78.3058569226583 \tabularnewline
0.48 & 10439.2371617721 & 78.9781869961458 \tabularnewline
0.49 & 10452.7705325609 & 79.8882290594606 \tabularnewline
0.5 & 10466.4165696519 & 80.9078306398646 \tabularnewline
0.51 & 10480.1816178868 & 81.8426078414282 \tabularnewline
0.52 & 10494.0492894778 & 82.5403504371034 \tabularnewline
0.53 & 10507.9824987449 & 82.8662895731932 \tabularnewline
0.54 & 10521.9278705716 & 82.7450192034388 \tabularnewline
0.55 & 10535.8219899015 & 82.1282332146602 \tabularnewline
0.56 & 10549.5987584927 & 81.0141687108166 \tabularnewline
0.57 & 10563.1970181119 & 79.4807838318167 \tabularnewline
0.58 & 10576.5675902162 & 77.6157811628815 \tabularnewline
0.59 & 10589.6789638515 & 75.538675849603 \tabularnewline
0.6 & 10602.5210210551 & 73.4267962325614 \tabularnewline
0.61 & 10615.1064030706 & 71.4274562165892 \tabularnewline
0.62 & 10627.4693698693 & 69.6864134052786 \tabularnewline
0.63 & 10639.6622683196 & 68.3074204349445 \tabularnewline
0.64 & 10651.7499798277 & 67.3789623546221 \tabularnewline
0.65 & 10663.8029462936 & 66.8898729693741 \tabularnewline
0.66 & 10675.8895554186 & 66.8331550273454 \tabularnewline
0.67 & 10688.0687877078 & 67.0890241214549 \tabularnewline
0.68 & 10700.3840785636 & 67.5483093978224 \tabularnewline
0.69 & 10712.8593284684 & 68.0623186653952 \tabularnewline
0.7 & 10725.4979109942 & 68.4735235768593 \tabularnewline
0.71 & 10738.2853998093 & 68.6699599887703 \tabularnewline
0.72 & 10751.1965834191 & 68.561699686136 \tabularnewline
0.73 & 10764.2071747086 & 68.1387615949756 \tabularnewline
0.74 & 10777.3104427861 & 67.474527432503 \tabularnewline
0.75 & 10790.5387471602 & 66.7333214474643 \tabularnewline
0.76 & 10803.9895378230 & 66.246981737926 \tabularnewline
0.77 & 10817.8546638137 & 66.4730122422181 \tabularnewline
0.78 & 10832.4507019759 & 68.046981770117 \tabularnewline
0.79 & 10848.2465290945 & 71.7511891825314 \tabularnewline
0.8 & 10865.882899297 & 78.4486315046414 \tabularnewline
0.81 & 10886.1782227707 & 88.9196992765297 \tabularnewline
0.82 & 10910.1164012065 & 103.677304917904 \tabularnewline
0.83 & 10938.817853295 & 122.842699893775 \tabularnewline
0.84 & 10973.5042840254 & 146.118621864564 \tabularnewline
0.85 & 11015.4795783754 & 172.867084670357 \tabularnewline
0.86 & 11066.1581444177 & 202.351240901872 \tabularnewline
0.87 & 11127.1692201087 & 234.218620470374 \tabularnewline
0.88 & 11200.5414046781 & 269.006363834173 \tabularnewline
0.89 & 11288.9221439979 & 308.517349014425 \tabularnewline
0.9 & 11395.7239237972 & 355.415705690934 \tabularnewline
0.91 & 11525.0486879504 & 411.695128236957 \tabularnewline
0.92 & 11681.2827772838 & 476.383051995396 \tabularnewline
0.93 & 11868.4255977195 & 543.70103044219 \tabularnewline
0.94 & 12089.4693032222 & 603.309561188664 \tabularnewline
0.95 & 12346.1900464509 & 643.682697680812 \tabularnewline
0.96 & 12638.9211820313 & 658.989451694093 \tabularnewline
0.97 & 12963.8136834444 & 658.38618071229 \tabularnewline
0.98 & 13303.4218520790 & 669.471985897264 \tabularnewline
0.99 & 13611.5264922187 & 714.373198642714 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19709&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]9126.33517654276[/C][C]74.94861192908[/C][/ROW]
[ROW][C]0.02[/C][C]9170.82205991521[/C][C]115.920323329112[/C][/ROW]
[ROW][C]0.03[/C][C]9232.14064811326[/C][C]157.039100575474[/C][/ROW]
[ROW][C]0.04[/C][C]9304.35255830025[/C][C]188.553533423985[/C][/ROW]
[ROW][C]0.05[/C][C]9381.66050287053[/C][C]206.758564674422[/C][/ROW]
[ROW][C]0.06[/C][C]9459.01046713178[/C][C]210.907174737959[/C][/ROW]
[ROW][C]0.07[/C][C]9532.42166218904[/C][C]202.734149136962[/C][/ROW]
[ROW][C]0.08[/C][C]9599.23532040266[/C][C]186.277355698808[/C][/ROW]
[ROW][C]0.09[/C][C]9658.18119437576[/C][C]166.501867367863[/C][/ROW]
[ROW][C]0.1[/C][C]9709.19232769118[/C][C]147.621769521320[/C][/ROW]
[ROW][C]0.11[/C][C]9753.0265811136[/C][C]131.989476811480[/C][/ROW]
[ROW][C]0.12[/C][C]9790.83517698197[/C][C]119.973491588369[/C][/ROW]
[ROW][C]0.13[/C][C]9823.81196174717[/C][C]110.767462716204[/C][/ROW]
[ROW][C]0.14[/C][C]9852.99082853378[/C][C]103.355972107700[/C][/ROW]
[ROW][C]0.15[/C][C]9879.18518410085[/C][C]97.1040869691877[/C][/ROW]
[ROW][C]0.16[/C][C]9903.01896612067[/C][C]91.8724104147151[/C][/ROW]
[ROW][C]0.17[/C][C]9924.990990546[/C][C]87.811835308924[/C][/ROW]
[ROW][C]0.18[/C][C]9945.5308767723[/C][C]85.1763784674898[/C][/ROW]
[ROW][C]0.19[/C][C]9965.02831710323[/C][C]84.0843326257743[/C][/ROW]
[ROW][C]0.2[/C][C]9983.8361736406[/C][C]84.4603743563675[/C][/ROW]
[ROW][C]0.21[/C][C]10002.2575890649[/C][C]86.0099116793167[/C][/ROW]
[ROW][C]0.22[/C][C]10020.5291347464[/C][C]88.302125542407[/C][/ROW]
[ROW][C]0.23[/C][C]10038.8092057663[/C][C]90.8568548251492[/C][/ROW]
[ROW][C]0.24[/C][C]10057.1764211860[/C][C]93.271396491626[/C][/ROW]
[ROW][C]0.25[/C][C]10075.6386292798[/C][C]95.1802379033552[/C][/ROW]
[ROW][C]0.26[/C][C]10094.1501359888[/C][C]96.428778220377[/C][/ROW]
[ROW][C]0.27[/C][C]10112.6331804764[/C][C]96.9574226952634[/C][/ROW]
[ROW][C]0.28[/C][C]10130.9993474732[/C][C]96.8287995022713[/C][/ROW]
[ROW][C]0.29[/C][C]10149.1672592277[/C][C]96.2264618002136[/C][/ROW]
[ROW][C]0.3[/C][C]10167.0741891201[/C][C]95.327336384555[/C][/ROW]
[ROW][C]0.31[/C][C]10184.6808117680[/C][C]94.3130411852809[/C][/ROW]
[ROW][C]0.32[/C][C]10201.9697899182[/C][C]93.3080821256555[/C][/ROW]
[ROW][C]0.33[/C][C]10218.9400038678[/C][C]92.3603456191593[/C][/ROW]
[ROW][C]0.34[/C][C]10235.5987812993[/C][C]91.504620601875[/C][/ROW]
[ROW][C]0.35[/C][C]10251.9544546918[/C][C]90.6403233505702[/C][/ROW]
[ROW][C]0.36[/C][C]10268.0110613874[/C][C]89.7083842506736[/C][/ROW]
[ROW][C]0.37[/C][C]10283.7661966884[/C][C]88.6245966981783[/C][/ROW]
[ROW][C]0.38[/C][C]10299.2121506703[/C][C]87.3553197333422[/C][/ROW]
[ROW][C]0.39[/C][C]10314.3396970780[/C][C]85.8902654134722[/C][/ROW]
[ROW][C]0.4[/C][C]10329.1433884902[/C][C]84.2880841937152[/C][/ROW]
[ROW][C]0.41[/C][C]10343.6270014664[/C][C]82.6363270789638[/C][/ROW]
[ROW][C]0.42[/C][C]10357.8078554264[/C][C]81.0680051710638[/C][/ROW]
[ROW][C]0.43[/C][C]10371.7190365770[/C][C]79.7131822732307[/C][/ROW]
[ROW][C]0.44[/C][C]10385.4090039330[/C][C]78.701127775062[/C][/ROW]
[ROW][C]0.45[/C][C]10398.9385440099[/C][C]78.1107561069595[/C][/ROW]
[ROW][C]0.46[/C][C]10412.3754905805[/C][C]77.9776246011486[/C][/ROW]
[ROW][C]0.47[/C][C]10425.7879729299[/C][C]78.3058569226583[/C][/ROW]
[ROW][C]0.48[/C][C]10439.2371617721[/C][C]78.9781869961458[/C][/ROW]
[ROW][C]0.49[/C][C]10452.7705325609[/C][C]79.8882290594606[/C][/ROW]
[ROW][C]0.5[/C][C]10466.4165696519[/C][C]80.9078306398646[/C][/ROW]
[ROW][C]0.51[/C][C]10480.1816178868[/C][C]81.8426078414282[/C][/ROW]
[ROW][C]0.52[/C][C]10494.0492894778[/C][C]82.5403504371034[/C][/ROW]
[ROW][C]0.53[/C][C]10507.9824987449[/C][C]82.8662895731932[/C][/ROW]
[ROW][C]0.54[/C][C]10521.9278705716[/C][C]82.7450192034388[/C][/ROW]
[ROW][C]0.55[/C][C]10535.8219899015[/C][C]82.1282332146602[/C][/ROW]
[ROW][C]0.56[/C][C]10549.5987584927[/C][C]81.0141687108166[/C][/ROW]
[ROW][C]0.57[/C][C]10563.1970181119[/C][C]79.4807838318167[/C][/ROW]
[ROW][C]0.58[/C][C]10576.5675902162[/C][C]77.6157811628815[/C][/ROW]
[ROW][C]0.59[/C][C]10589.6789638515[/C][C]75.538675849603[/C][/ROW]
[ROW][C]0.6[/C][C]10602.5210210551[/C][C]73.4267962325614[/C][/ROW]
[ROW][C]0.61[/C][C]10615.1064030706[/C][C]71.4274562165892[/C][/ROW]
[ROW][C]0.62[/C][C]10627.4693698693[/C][C]69.6864134052786[/C][/ROW]
[ROW][C]0.63[/C][C]10639.6622683196[/C][C]68.3074204349445[/C][/ROW]
[ROW][C]0.64[/C][C]10651.7499798277[/C][C]67.3789623546221[/C][/ROW]
[ROW][C]0.65[/C][C]10663.8029462936[/C][C]66.8898729693741[/C][/ROW]
[ROW][C]0.66[/C][C]10675.8895554186[/C][C]66.8331550273454[/C][/ROW]
[ROW][C]0.67[/C][C]10688.0687877078[/C][C]67.0890241214549[/C][/ROW]
[ROW][C]0.68[/C][C]10700.3840785636[/C][C]67.5483093978224[/C][/ROW]
[ROW][C]0.69[/C][C]10712.8593284684[/C][C]68.0623186653952[/C][/ROW]
[ROW][C]0.7[/C][C]10725.4979109942[/C][C]68.4735235768593[/C][/ROW]
[ROW][C]0.71[/C][C]10738.2853998093[/C][C]68.6699599887703[/C][/ROW]
[ROW][C]0.72[/C][C]10751.1965834191[/C][C]68.561699686136[/C][/ROW]
[ROW][C]0.73[/C][C]10764.2071747086[/C][C]68.1387615949756[/C][/ROW]
[ROW][C]0.74[/C][C]10777.3104427861[/C][C]67.474527432503[/C][/ROW]
[ROW][C]0.75[/C][C]10790.5387471602[/C][C]66.7333214474643[/C][/ROW]
[ROW][C]0.76[/C][C]10803.9895378230[/C][C]66.246981737926[/C][/ROW]
[ROW][C]0.77[/C][C]10817.8546638137[/C][C]66.4730122422181[/C][/ROW]
[ROW][C]0.78[/C][C]10832.4507019759[/C][C]68.046981770117[/C][/ROW]
[ROW][C]0.79[/C][C]10848.2465290945[/C][C]71.7511891825314[/C][/ROW]
[ROW][C]0.8[/C][C]10865.882899297[/C][C]78.4486315046414[/C][/ROW]
[ROW][C]0.81[/C][C]10886.1782227707[/C][C]88.9196992765297[/C][/ROW]
[ROW][C]0.82[/C][C]10910.1164012065[/C][C]103.677304917904[/C][/ROW]
[ROW][C]0.83[/C][C]10938.817853295[/C][C]122.842699893775[/C][/ROW]
[ROW][C]0.84[/C][C]10973.5042840254[/C][C]146.118621864564[/C][/ROW]
[ROW][C]0.85[/C][C]11015.4795783754[/C][C]172.867084670357[/C][/ROW]
[ROW][C]0.86[/C][C]11066.1581444177[/C][C]202.351240901872[/C][/ROW]
[ROW][C]0.87[/C][C]11127.1692201087[/C][C]234.218620470374[/C][/ROW]
[ROW][C]0.88[/C][C]11200.5414046781[/C][C]269.006363834173[/C][/ROW]
[ROW][C]0.89[/C][C]11288.9221439979[/C][C]308.517349014425[/C][/ROW]
[ROW][C]0.9[/C][C]11395.7239237972[/C][C]355.415705690934[/C][/ROW]
[ROW][C]0.91[/C][C]11525.0486879504[/C][C]411.695128236957[/C][/ROW]
[ROW][C]0.92[/C][C]11681.2827772838[/C][C]476.383051995396[/C][/ROW]
[ROW][C]0.93[/C][C]11868.4255977195[/C][C]543.70103044219[/C][/ROW]
[ROW][C]0.94[/C][C]12089.4693032222[/C][C]603.309561188664[/C][/ROW]
[ROW][C]0.95[/C][C]12346.1900464509[/C][C]643.682697680812[/C][/ROW]
[ROW][C]0.96[/C][C]12638.9211820313[/C][C]658.989451694093[/C][/ROW]
[ROW][C]0.97[/C][C]12963.8136834444[/C][C]658.38618071229[/C][/ROW]
[ROW][C]0.98[/C][C]13303.4218520790[/C][C]669.471985897264[/C][/ROW]
[ROW][C]0.99[/C][C]13611.5264922187[/C][C]714.373198642714[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19709&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19709&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
0.019126.3351765427674.94861192908
0.029170.82205991521115.920323329112
0.039232.14064811326157.039100575474
0.049304.35255830025188.553533423985
0.059381.66050287053206.758564674422
0.069459.01046713178210.907174737959
0.079532.42166218904202.734149136962
0.089599.23532040266186.277355698808
0.099658.18119437576166.501867367863
0.19709.19232769118147.621769521320
0.119753.0265811136131.989476811480
0.129790.83517698197119.973491588369
0.139823.81196174717110.767462716204
0.149852.99082853378103.355972107700
0.159879.1851841008597.1040869691877
0.169903.0189661206791.8724104147151
0.179924.99099054687.811835308924
0.189945.530876772385.1763784674898
0.199965.0283171032384.0843326257743
0.29983.836173640684.4603743563675
0.2110002.257589064986.0099116793167
0.2210020.529134746488.302125542407
0.2310038.809205766390.8568548251492
0.2410057.176421186093.271396491626
0.2510075.638629279895.1802379033552
0.2610094.150135988896.428778220377
0.2710112.633180476496.9574226952634
0.2810130.999347473296.8287995022713
0.2910149.167259227796.2264618002136
0.310167.074189120195.327336384555
0.3110184.680811768094.3130411852809
0.3210201.969789918293.3080821256555
0.3310218.940003867892.3603456191593
0.3410235.598781299391.504620601875
0.3510251.954454691890.6403233505702
0.3610268.011061387489.7083842506736
0.3710283.766196688488.6245966981783
0.3810299.212150670387.3553197333422
0.3910314.339697078085.8902654134722
0.410329.143388490284.2880841937152
0.4110343.627001466482.6363270789638
0.4210357.807855426481.0680051710638
0.4310371.719036577079.7131822732307
0.4410385.409003933078.701127775062
0.4510398.938544009978.1107561069595
0.4610412.375490580577.9776246011486
0.4710425.787972929978.3058569226583
0.4810439.237161772178.9781869961458
0.4910452.770532560979.8882290594606
0.510466.416569651980.9078306398646
0.5110480.181617886881.8426078414282
0.5210494.049289477882.5403504371034
0.5310507.982498744982.8662895731932
0.5410521.927870571682.7450192034388
0.5510535.821989901582.1282332146602
0.5610549.598758492781.0141687108166
0.5710563.197018111979.4807838318167
0.5810576.567590216277.6157811628815
0.5910589.678963851575.538675849603
0.610602.521021055173.4267962325614
0.6110615.106403070671.4274562165892
0.6210627.469369869369.6864134052786
0.6310639.662268319668.3074204349445
0.6410651.749979827767.3789623546221
0.6510663.802946293666.8898729693741
0.6610675.889555418666.8331550273454
0.6710688.068787707867.0890241214549
0.6810700.384078563667.5483093978224
0.6910712.859328468468.0623186653952
0.710725.497910994268.4735235768593
0.7110738.285399809368.6699599887703
0.7210751.196583419168.561699686136
0.7310764.207174708668.1387615949756
0.7410777.310442786167.474527432503
0.7510790.538747160266.7333214474643
0.7610803.989537823066.246981737926
0.7710817.854663813766.4730122422181
0.7810832.450701975968.046981770117
0.7910848.246529094571.7511891825314
0.810865.88289929778.4486315046414
0.8110886.178222770788.9196992765297
0.8210910.1164012065103.677304917904
0.8310938.817853295122.842699893775
0.8410973.5042840254146.118621864564
0.8511015.4795783754172.867084670357
0.8611066.1581444177202.351240901872
0.8711127.1692201087234.218620470374
0.8811200.5414046781269.006363834173
0.8911288.9221439979308.517349014425
0.911395.7239237972355.415705690934
0.9111525.0486879504411.695128236957
0.9211681.2827772838476.383051995396
0.9311868.4255977195543.70103044219
0.9412089.4693032222603.309561188664
0.9512346.1900464509643.682697680812
0.9612638.9211820313658.989451694093
0.9712963.8136834444658.38618071229
0.9813303.4218520790669.471985897264
0.9913611.5264922187714.373198642714


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')