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Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationTue, 09 Mar 2010 08:50:15 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Mar/09/t1268149992ywu5vv6ajjinsa3.htm/, Retrieved Wed, 19 Jan 2022 11:15:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=74200, Retrieved Wed, 19 Jan 2022 11:15:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W42
Estimated Impact140
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [Frequentietabel] [2010-02-08 18:35:02] [376ebd6f62706e95ba27a8145e16298d]
- RMPD  [Kernel Density Estimation] [] [2010-02-23 17:46:26] [376ebd6f62706e95ba27a8145e16298d]
- RMP       [Harrell-Davis Quantiles] [] [2010-03-09 15:50:15] [4b0ce05bd143e68bee12076814fe6457] [Current]
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Dataseries X:
8027.7
8059.6
8059.5
7988.9
7950.2
8003.8
8037.5
8069
8157.6
8244.3
8329.4
8417
8432.5
8486.4
8531.1
8643.8
8727.9
8847.3
8904.3
9003.2
9025.3
9044.7
9120.7
9184.3
9247.2
9407.1
9488.9
9592.5
9666.2
9809.6
9932.7
10008.9
10103.4
10194.3
10328.8
10507.6
10601.2
10684
10819.9
11014.3
11043
11258.5
11267.9
11334.5
11297.2
11371.3
11340.1
11380.1
11477.9
11538.8
11596.4
11598.8
11645.8
11738.7
11935.5
12042.8
12127.6
12213.8
12303.5
12410.3
12534.1
12587.5
12683.2
12748.7
12915.9
12962.5
12965.9
13060.7
13099.9
13204
13321.1
13391.2
13366.9
13415.3
13324.6
13141.9
12925.4
12901.5
12973
13155




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74200&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74200&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74200&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Harrell-Davis Quantiles
quantilesvaluestandard error
0.017963.5036080376532.4106447874658
0.027982.4461315251627.5224246038997
0.038000.7725580163727.0176616362384
0.048017.3352491659830.0863755767065
0.058033.5241203137636.9938449710254
0.068051.2392547504949.1945000525228
0.078072.3004997231367.0367951863188
0.088098.2099609756889.1181550423678
0.098129.88073229712112.85666864436
0.18167.45402996874135.444098517736
0.118210.3400514695154.782292497938
0.128257.47231916733170.030025309084
0.138307.6565483895181.681617743764
0.148359.87293534681191.042539132130
0.158413.43818633772199.588340384986
0.168468.0088653117208.322041254356
0.178523.47089532027217.410348864019
0.188579.78939555728226.410680837207
0.198636.88720692544234.538689725002
0.28694.59194497933241.093682695828
0.218752.65682923125245.8909900358
0.228810.83325692923249.242088832826
0.238868.95991903164251.946615342509
0.248927.03447750873255.105725341783
0.258985.24525605029259.855744163862
0.269043.95605431081267.061799888626
0.279103.65155400177277.077833410751
0.289164.86017412928289.819704974073
0.299228.07429183538304.758282256065
0.39293.68513218045321.109025539711
0.319361.94329678839337.994550492864
0.329432.94824746828354.642845949290
0.339506.66321021357370.497649679735
0.349582.94730997682385.173122006498
0.359661.5948069215398.551184771899
0.369742.37184770338410.619689370397
0.379825.0434611575421.536095585568
0.389909.38673895807431.380778064443
0.399995.18945038864440.233714376786
0.410082.2361691550448.024313812624
0.4110170.2860199034454.494434348776
0.4210259.0472853308459.300542565809
0.4310348.1544048008461.934917945372
0.4410437.1524706713461.835153053022
0.4510525.4933323414458.44794061625
0.4610612.5459748435451.341626637139
0.4710697.6220533848440.228498843135
0.4810780.0154511436425.108033999682
0.4910859.0526507260406.205177228374
0.510934.1488203994384.116048120953
0.5111004.8631420320359.698785945592
0.5211070.9463900031334.106160185211
0.5311132.3743553901308.62591520723
0.5411189.3624308943284.608672564788
0.5511242.3592776563263.386591835596
0.5611292.0204678890246.089475835015
0.5711339.1656786853233.603586022287
0.5811384.7248026545226.410276952395
0.5911429.6789035567224.679520032725
0.611475.0013315647228.070506779359
0.6111521.6029472721236.039098414652
0.6211570.2839164326247.745421029123
0.6311621.6935055227262.176997836612
0.6411676.2990070526278.248366046773
0.6511734.3652029528294.821738037292
0.6611795.9461253701310.755679064678
0.6711860.8906715465325.023541135275
0.6811928.8624501898336.734418614107
0.6911999.3721110296345.255188486542
0.712071.8178813995350.230675624156
0.7112145.5279946085351.530708309773
0.7212219.7980510584349.243971180835
0.7312293.9176682455343.551236897658
0.7412367.1840237331334.686265945592
0.7512438.9043999497322.824555737588
0.7612508.3943979266308.104464689159
0.7712574.9816203440290.623872615342
0.7812638.0249173452270.590312423872
0.7912696.9558047798248.307004238548
0.812751.3414222827224.412467105890
0.8112800.9588079488199.876887416899
0.8212845.8612828749175.946132277276
0.8312886.413397319154.037989456264
0.8412923.2749605539135.494756924712
0.8512957.3285262060121.263257923876
0.8612989.5650624838111.560152452363
0.8713020.9605871972105.822899527080
0.8813052.3802597422102.954649199851
0.8913084.5273886243101.858842368416
0.913117.9180725429101.767734714249
0.9113152.8322905482102.079970308877
0.9213189.2043639942101.82147460371
0.9313226.485448475499.336358505107
0.9413263.598570919492.7834310011366
0.9513299.121669321981.3876893301742
0.9613331.707066711266.317565378766
0.9713360.504867158150.2349157143869
0.9813385.090277974635.9592188232381
0.9913404.363076434426.5113318687416

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 7963.50360803765 & 32.4106447874658 \tabularnewline
0.02 & 7982.44613152516 & 27.5224246038997 \tabularnewline
0.03 & 8000.77255801637 & 27.0176616362384 \tabularnewline
0.04 & 8017.33524916598 & 30.0863755767065 \tabularnewline
0.05 & 8033.52412031376 & 36.9938449710254 \tabularnewline
0.06 & 8051.23925475049 & 49.1945000525228 \tabularnewline
0.07 & 8072.30049972313 & 67.0367951863188 \tabularnewline
0.08 & 8098.20996097568 & 89.1181550423678 \tabularnewline
0.09 & 8129.88073229712 & 112.85666864436 \tabularnewline
0.1 & 8167.45402996874 & 135.444098517736 \tabularnewline
0.11 & 8210.3400514695 & 154.782292497938 \tabularnewline
0.12 & 8257.47231916733 & 170.030025309084 \tabularnewline
0.13 & 8307.6565483895 & 181.681617743764 \tabularnewline
0.14 & 8359.87293534681 & 191.042539132130 \tabularnewline
0.15 & 8413.43818633772 & 199.588340384986 \tabularnewline
0.16 & 8468.0088653117 & 208.322041254356 \tabularnewline
0.17 & 8523.47089532027 & 217.410348864019 \tabularnewline
0.18 & 8579.78939555728 & 226.410680837207 \tabularnewline
0.19 & 8636.88720692544 & 234.538689725002 \tabularnewline
0.2 & 8694.59194497933 & 241.093682695828 \tabularnewline
0.21 & 8752.65682923125 & 245.8909900358 \tabularnewline
0.22 & 8810.83325692923 & 249.242088832826 \tabularnewline
0.23 & 8868.95991903164 & 251.946615342509 \tabularnewline
0.24 & 8927.03447750873 & 255.105725341783 \tabularnewline
0.25 & 8985.24525605029 & 259.855744163862 \tabularnewline
0.26 & 9043.95605431081 & 267.061799888626 \tabularnewline
0.27 & 9103.65155400177 & 277.077833410751 \tabularnewline
0.28 & 9164.86017412928 & 289.819704974073 \tabularnewline
0.29 & 9228.07429183538 & 304.758282256065 \tabularnewline
0.3 & 9293.68513218045 & 321.109025539711 \tabularnewline
0.31 & 9361.94329678839 & 337.994550492864 \tabularnewline
0.32 & 9432.94824746828 & 354.642845949290 \tabularnewline
0.33 & 9506.66321021357 & 370.497649679735 \tabularnewline
0.34 & 9582.94730997682 & 385.173122006498 \tabularnewline
0.35 & 9661.5948069215 & 398.551184771899 \tabularnewline
0.36 & 9742.37184770338 & 410.619689370397 \tabularnewline
0.37 & 9825.0434611575 & 421.536095585568 \tabularnewline
0.38 & 9909.38673895807 & 431.380778064443 \tabularnewline
0.39 & 9995.18945038864 & 440.233714376786 \tabularnewline
0.4 & 10082.2361691550 & 448.024313812624 \tabularnewline
0.41 & 10170.2860199034 & 454.494434348776 \tabularnewline
0.42 & 10259.0472853308 & 459.300542565809 \tabularnewline
0.43 & 10348.1544048008 & 461.934917945372 \tabularnewline
0.44 & 10437.1524706713 & 461.835153053022 \tabularnewline
0.45 & 10525.4933323414 & 458.44794061625 \tabularnewline
0.46 & 10612.5459748435 & 451.341626637139 \tabularnewline
0.47 & 10697.6220533848 & 440.228498843135 \tabularnewline
0.48 & 10780.0154511436 & 425.108033999682 \tabularnewline
0.49 & 10859.0526507260 & 406.205177228374 \tabularnewline
0.5 & 10934.1488203994 & 384.116048120953 \tabularnewline
0.51 & 11004.8631420320 & 359.698785945592 \tabularnewline
0.52 & 11070.9463900031 & 334.106160185211 \tabularnewline
0.53 & 11132.3743553901 & 308.62591520723 \tabularnewline
0.54 & 11189.3624308943 & 284.608672564788 \tabularnewline
0.55 & 11242.3592776563 & 263.386591835596 \tabularnewline
0.56 & 11292.0204678890 & 246.089475835015 \tabularnewline
0.57 & 11339.1656786853 & 233.603586022287 \tabularnewline
0.58 & 11384.7248026545 & 226.410276952395 \tabularnewline
0.59 & 11429.6789035567 & 224.679520032725 \tabularnewline
0.6 & 11475.0013315647 & 228.070506779359 \tabularnewline
0.61 & 11521.6029472721 & 236.039098414652 \tabularnewline
0.62 & 11570.2839164326 & 247.745421029123 \tabularnewline
0.63 & 11621.6935055227 & 262.176997836612 \tabularnewline
0.64 & 11676.2990070526 & 278.248366046773 \tabularnewline
0.65 & 11734.3652029528 & 294.821738037292 \tabularnewline
0.66 & 11795.9461253701 & 310.755679064678 \tabularnewline
0.67 & 11860.8906715465 & 325.023541135275 \tabularnewline
0.68 & 11928.8624501898 & 336.734418614107 \tabularnewline
0.69 & 11999.3721110296 & 345.255188486542 \tabularnewline
0.7 & 12071.8178813995 & 350.230675624156 \tabularnewline
0.71 & 12145.5279946085 & 351.530708309773 \tabularnewline
0.72 & 12219.7980510584 & 349.243971180835 \tabularnewline
0.73 & 12293.9176682455 & 343.551236897658 \tabularnewline
0.74 & 12367.1840237331 & 334.686265945592 \tabularnewline
0.75 & 12438.9043999497 & 322.824555737588 \tabularnewline
0.76 & 12508.3943979266 & 308.104464689159 \tabularnewline
0.77 & 12574.9816203440 & 290.623872615342 \tabularnewline
0.78 & 12638.0249173452 & 270.590312423872 \tabularnewline
0.79 & 12696.9558047798 & 248.307004238548 \tabularnewline
0.8 & 12751.3414222827 & 224.412467105890 \tabularnewline
0.81 & 12800.9588079488 & 199.876887416899 \tabularnewline
0.82 & 12845.8612828749 & 175.946132277276 \tabularnewline
0.83 & 12886.413397319 & 154.037989456264 \tabularnewline
0.84 & 12923.2749605539 & 135.494756924712 \tabularnewline
0.85 & 12957.3285262060 & 121.263257923876 \tabularnewline
0.86 & 12989.5650624838 & 111.560152452363 \tabularnewline
0.87 & 13020.9605871972 & 105.822899527080 \tabularnewline
0.88 & 13052.3802597422 & 102.954649199851 \tabularnewline
0.89 & 13084.5273886243 & 101.858842368416 \tabularnewline
0.9 & 13117.9180725429 & 101.767734714249 \tabularnewline
0.91 & 13152.8322905482 & 102.079970308877 \tabularnewline
0.92 & 13189.2043639942 & 101.82147460371 \tabularnewline
0.93 & 13226.4854484754 & 99.336358505107 \tabularnewline
0.94 & 13263.5985709194 & 92.7834310011366 \tabularnewline
0.95 & 13299.1216693219 & 81.3876893301742 \tabularnewline
0.96 & 13331.7070667112 & 66.317565378766 \tabularnewline
0.97 & 13360.5048671581 & 50.2349157143869 \tabularnewline
0.98 & 13385.0902779746 & 35.9592188232381 \tabularnewline
0.99 & 13404.3630764344 & 26.5113318687416 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74200&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]7963.50360803765[/C][C]32.4106447874658[/C][/ROW]
[ROW][C]0.02[/C][C]7982.44613152516[/C][C]27.5224246038997[/C][/ROW]
[ROW][C]0.03[/C][C]8000.77255801637[/C][C]27.0176616362384[/C][/ROW]
[ROW][C]0.04[/C][C]8017.33524916598[/C][C]30.0863755767065[/C][/ROW]
[ROW][C]0.05[/C][C]8033.52412031376[/C][C]36.9938449710254[/C][/ROW]
[ROW][C]0.06[/C][C]8051.23925475049[/C][C]49.1945000525228[/C][/ROW]
[ROW][C]0.07[/C][C]8072.30049972313[/C][C]67.0367951863188[/C][/ROW]
[ROW][C]0.08[/C][C]8098.20996097568[/C][C]89.1181550423678[/C][/ROW]
[ROW][C]0.09[/C][C]8129.88073229712[/C][C]112.85666864436[/C][/ROW]
[ROW][C]0.1[/C][C]8167.45402996874[/C][C]135.444098517736[/C][/ROW]
[ROW][C]0.11[/C][C]8210.3400514695[/C][C]154.782292497938[/C][/ROW]
[ROW][C]0.12[/C][C]8257.47231916733[/C][C]170.030025309084[/C][/ROW]
[ROW][C]0.13[/C][C]8307.6565483895[/C][C]181.681617743764[/C][/ROW]
[ROW][C]0.14[/C][C]8359.87293534681[/C][C]191.042539132130[/C][/ROW]
[ROW][C]0.15[/C][C]8413.43818633772[/C][C]199.588340384986[/C][/ROW]
[ROW][C]0.16[/C][C]8468.0088653117[/C][C]208.322041254356[/C][/ROW]
[ROW][C]0.17[/C][C]8523.47089532027[/C][C]217.410348864019[/C][/ROW]
[ROW][C]0.18[/C][C]8579.78939555728[/C][C]226.410680837207[/C][/ROW]
[ROW][C]0.19[/C][C]8636.88720692544[/C][C]234.538689725002[/C][/ROW]
[ROW][C]0.2[/C][C]8694.59194497933[/C][C]241.093682695828[/C][/ROW]
[ROW][C]0.21[/C][C]8752.65682923125[/C][C]245.8909900358[/C][/ROW]
[ROW][C]0.22[/C][C]8810.83325692923[/C][C]249.242088832826[/C][/ROW]
[ROW][C]0.23[/C][C]8868.95991903164[/C][C]251.946615342509[/C][/ROW]
[ROW][C]0.24[/C][C]8927.03447750873[/C][C]255.105725341783[/C][/ROW]
[ROW][C]0.25[/C][C]8985.24525605029[/C][C]259.855744163862[/C][/ROW]
[ROW][C]0.26[/C][C]9043.95605431081[/C][C]267.061799888626[/C][/ROW]
[ROW][C]0.27[/C][C]9103.65155400177[/C][C]277.077833410751[/C][/ROW]
[ROW][C]0.28[/C][C]9164.86017412928[/C][C]289.819704974073[/C][/ROW]
[ROW][C]0.29[/C][C]9228.07429183538[/C][C]304.758282256065[/C][/ROW]
[ROW][C]0.3[/C][C]9293.68513218045[/C][C]321.109025539711[/C][/ROW]
[ROW][C]0.31[/C][C]9361.94329678839[/C][C]337.994550492864[/C][/ROW]
[ROW][C]0.32[/C][C]9432.94824746828[/C][C]354.642845949290[/C][/ROW]
[ROW][C]0.33[/C][C]9506.66321021357[/C][C]370.497649679735[/C][/ROW]
[ROW][C]0.34[/C][C]9582.94730997682[/C][C]385.173122006498[/C][/ROW]
[ROW][C]0.35[/C][C]9661.5948069215[/C][C]398.551184771899[/C][/ROW]
[ROW][C]0.36[/C][C]9742.37184770338[/C][C]410.619689370397[/C][/ROW]
[ROW][C]0.37[/C][C]9825.0434611575[/C][C]421.536095585568[/C][/ROW]
[ROW][C]0.38[/C][C]9909.38673895807[/C][C]431.380778064443[/C][/ROW]
[ROW][C]0.39[/C][C]9995.18945038864[/C][C]440.233714376786[/C][/ROW]
[ROW][C]0.4[/C][C]10082.2361691550[/C][C]448.024313812624[/C][/ROW]
[ROW][C]0.41[/C][C]10170.2860199034[/C][C]454.494434348776[/C][/ROW]
[ROW][C]0.42[/C][C]10259.0472853308[/C][C]459.300542565809[/C][/ROW]
[ROW][C]0.43[/C][C]10348.1544048008[/C][C]461.934917945372[/C][/ROW]
[ROW][C]0.44[/C][C]10437.1524706713[/C][C]461.835153053022[/C][/ROW]
[ROW][C]0.45[/C][C]10525.4933323414[/C][C]458.44794061625[/C][/ROW]
[ROW][C]0.46[/C][C]10612.5459748435[/C][C]451.341626637139[/C][/ROW]
[ROW][C]0.47[/C][C]10697.6220533848[/C][C]440.228498843135[/C][/ROW]
[ROW][C]0.48[/C][C]10780.0154511436[/C][C]425.108033999682[/C][/ROW]
[ROW][C]0.49[/C][C]10859.0526507260[/C][C]406.205177228374[/C][/ROW]
[ROW][C]0.5[/C][C]10934.1488203994[/C][C]384.116048120953[/C][/ROW]
[ROW][C]0.51[/C][C]11004.8631420320[/C][C]359.698785945592[/C][/ROW]
[ROW][C]0.52[/C][C]11070.9463900031[/C][C]334.106160185211[/C][/ROW]
[ROW][C]0.53[/C][C]11132.3743553901[/C][C]308.62591520723[/C][/ROW]
[ROW][C]0.54[/C][C]11189.3624308943[/C][C]284.608672564788[/C][/ROW]
[ROW][C]0.55[/C][C]11242.3592776563[/C][C]263.386591835596[/C][/ROW]
[ROW][C]0.56[/C][C]11292.0204678890[/C][C]246.089475835015[/C][/ROW]
[ROW][C]0.57[/C][C]11339.1656786853[/C][C]233.603586022287[/C][/ROW]
[ROW][C]0.58[/C][C]11384.7248026545[/C][C]226.410276952395[/C][/ROW]
[ROW][C]0.59[/C][C]11429.6789035567[/C][C]224.679520032725[/C][/ROW]
[ROW][C]0.6[/C][C]11475.0013315647[/C][C]228.070506779359[/C][/ROW]
[ROW][C]0.61[/C][C]11521.6029472721[/C][C]236.039098414652[/C][/ROW]
[ROW][C]0.62[/C][C]11570.2839164326[/C][C]247.745421029123[/C][/ROW]
[ROW][C]0.63[/C][C]11621.6935055227[/C][C]262.176997836612[/C][/ROW]
[ROW][C]0.64[/C][C]11676.2990070526[/C][C]278.248366046773[/C][/ROW]
[ROW][C]0.65[/C][C]11734.3652029528[/C][C]294.821738037292[/C][/ROW]
[ROW][C]0.66[/C][C]11795.9461253701[/C][C]310.755679064678[/C][/ROW]
[ROW][C]0.67[/C][C]11860.8906715465[/C][C]325.023541135275[/C][/ROW]
[ROW][C]0.68[/C][C]11928.8624501898[/C][C]336.734418614107[/C][/ROW]
[ROW][C]0.69[/C][C]11999.3721110296[/C][C]345.255188486542[/C][/ROW]
[ROW][C]0.7[/C][C]12071.8178813995[/C][C]350.230675624156[/C][/ROW]
[ROW][C]0.71[/C][C]12145.5279946085[/C][C]351.530708309773[/C][/ROW]
[ROW][C]0.72[/C][C]12219.7980510584[/C][C]349.243971180835[/C][/ROW]
[ROW][C]0.73[/C][C]12293.9176682455[/C][C]343.551236897658[/C][/ROW]
[ROW][C]0.74[/C][C]12367.1840237331[/C][C]334.686265945592[/C][/ROW]
[ROW][C]0.75[/C][C]12438.9043999497[/C][C]322.824555737588[/C][/ROW]
[ROW][C]0.76[/C][C]12508.3943979266[/C][C]308.104464689159[/C][/ROW]
[ROW][C]0.77[/C][C]12574.9816203440[/C][C]290.623872615342[/C][/ROW]
[ROW][C]0.78[/C][C]12638.0249173452[/C][C]270.590312423872[/C][/ROW]
[ROW][C]0.79[/C][C]12696.9558047798[/C][C]248.307004238548[/C][/ROW]
[ROW][C]0.8[/C][C]12751.3414222827[/C][C]224.412467105890[/C][/ROW]
[ROW][C]0.81[/C][C]12800.9588079488[/C][C]199.876887416899[/C][/ROW]
[ROW][C]0.82[/C][C]12845.8612828749[/C][C]175.946132277276[/C][/ROW]
[ROW][C]0.83[/C][C]12886.413397319[/C][C]154.037989456264[/C][/ROW]
[ROW][C]0.84[/C][C]12923.2749605539[/C][C]135.494756924712[/C][/ROW]
[ROW][C]0.85[/C][C]12957.3285262060[/C][C]121.263257923876[/C][/ROW]
[ROW][C]0.86[/C][C]12989.5650624838[/C][C]111.560152452363[/C][/ROW]
[ROW][C]0.87[/C][C]13020.9605871972[/C][C]105.822899527080[/C][/ROW]
[ROW][C]0.88[/C][C]13052.3802597422[/C][C]102.954649199851[/C][/ROW]
[ROW][C]0.89[/C][C]13084.5273886243[/C][C]101.858842368416[/C][/ROW]
[ROW][C]0.9[/C][C]13117.9180725429[/C][C]101.767734714249[/C][/ROW]
[ROW][C]0.91[/C][C]13152.8322905482[/C][C]102.079970308877[/C][/ROW]
[ROW][C]0.92[/C][C]13189.2043639942[/C][C]101.82147460371[/C][/ROW]
[ROW][C]0.93[/C][C]13226.4854484754[/C][C]99.336358505107[/C][/ROW]
[ROW][C]0.94[/C][C]13263.5985709194[/C][C]92.7834310011366[/C][/ROW]
[ROW][C]0.95[/C][C]13299.1216693219[/C][C]81.3876893301742[/C][/ROW]
[ROW][C]0.96[/C][C]13331.7070667112[/C][C]66.317565378766[/C][/ROW]
[ROW][C]0.97[/C][C]13360.5048671581[/C][C]50.2349157143869[/C][/ROW]
[ROW][C]0.98[/C][C]13385.0902779746[/C][C]35.9592188232381[/C][/ROW]
[ROW][C]0.99[/C][C]13404.3630764344[/C][C]26.5113318687416[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74200&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74200&T=1

As an alternative you can also use a QR Code:  

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

Harrell-Davis Quantiles
quantilesvaluestandard error
0.017963.5036080376532.4106447874658
0.027982.4461315251627.5224246038997
0.038000.7725580163727.0176616362384
0.048017.3352491659830.0863755767065
0.058033.5241203137636.9938449710254
0.068051.2392547504949.1945000525228
0.078072.3004997231367.0367951863188
0.088098.2099609756889.1181550423678
0.098129.88073229712112.85666864436
0.18167.45402996874135.444098517736
0.118210.3400514695154.782292497938
0.128257.47231916733170.030025309084
0.138307.6565483895181.681617743764
0.148359.87293534681191.042539132130
0.158413.43818633772199.588340384986
0.168468.0088653117208.322041254356
0.178523.47089532027217.410348864019
0.188579.78939555728226.410680837207
0.198636.88720692544234.538689725002
0.28694.59194497933241.093682695828
0.218752.65682923125245.8909900358
0.228810.83325692923249.242088832826
0.238868.95991903164251.946615342509
0.248927.03447750873255.105725341783
0.258985.24525605029259.855744163862
0.269043.95605431081267.061799888626
0.279103.65155400177277.077833410751
0.289164.86017412928289.819704974073
0.299228.07429183538304.758282256065
0.39293.68513218045321.109025539711
0.319361.94329678839337.994550492864
0.329432.94824746828354.642845949290
0.339506.66321021357370.497649679735
0.349582.94730997682385.173122006498
0.359661.5948069215398.551184771899
0.369742.37184770338410.619689370397
0.379825.0434611575421.536095585568
0.389909.38673895807431.380778064443
0.399995.18945038864440.233714376786
0.410082.2361691550448.024313812624
0.4110170.2860199034454.494434348776
0.4210259.0472853308459.300542565809
0.4310348.1544048008461.934917945372
0.4410437.1524706713461.835153053022
0.4510525.4933323414458.44794061625
0.4610612.5459748435451.341626637139
0.4710697.6220533848440.228498843135
0.4810780.0154511436425.108033999682
0.4910859.0526507260406.205177228374
0.510934.1488203994384.116048120953
0.5111004.8631420320359.698785945592
0.5211070.9463900031334.106160185211
0.5311132.3743553901308.62591520723
0.5411189.3624308943284.608672564788
0.5511242.3592776563263.386591835596
0.5611292.0204678890246.089475835015
0.5711339.1656786853233.603586022287
0.5811384.7248026545226.410276952395
0.5911429.6789035567224.679520032725
0.611475.0013315647228.070506779359
0.6111521.6029472721236.039098414652
0.6211570.2839164326247.745421029123
0.6311621.6935055227262.176997836612
0.6411676.2990070526278.248366046773
0.6511734.3652029528294.821738037292
0.6611795.9461253701310.755679064678
0.6711860.8906715465325.023541135275
0.6811928.8624501898336.734418614107
0.6911999.3721110296345.255188486542
0.712071.8178813995350.230675624156
0.7112145.5279946085351.530708309773
0.7212219.7980510584349.243971180835
0.7312293.9176682455343.551236897658
0.7412367.1840237331334.686265945592
0.7512438.9043999497322.824555737588
0.7612508.3943979266308.104464689159
0.7712574.9816203440290.623872615342
0.7812638.0249173452270.590312423872
0.7912696.9558047798248.307004238548
0.812751.3414222827224.412467105890
0.8112800.9588079488199.876887416899
0.8212845.8612828749175.946132277276
0.8312886.413397319154.037989456264
0.8412923.2749605539135.494756924712
0.8512957.3285262060121.263257923876
0.8612989.5650624838111.560152452363
0.8713020.9605871972105.822899527080
0.8813052.3802597422102.954649199851
0.8913084.5273886243101.858842368416
0.913117.9180725429101.767734714249
0.9113152.8322905482102.079970308877
0.9213189.2043639942101.82147460371
0.9313226.485448475499.336358505107
0.9413263.598570919492.7834310011366
0.9513299.121669321981.3876893301742
0.9613331.707066711266.317565378766
0.9713360.504867158150.2349157143869
0.9813385.090277974635.9592188232381
0.9913404.363076434426.5113318687416



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')