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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 computationTue, 14 Aug 2012 14:49:01 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Aug/14/t1344970607wa4bjdkhnjlphkv.htm/, Retrieved Thu, 02 May 2024 09:40:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=169336, Retrieved Thu, 02 May 2024 09:40:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSam De Maeyer
Estimated Impact101

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 1 Kwant...] [2012-08-14 18:49:01] [df2e1cb801e9c7e9e5c4a0dfd693d83a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
181896
181580
181234
180598
187123
186807
181896
178638
178954
178954
179269
179936
181580
179616
181580
179936
185158
187469
177656
175025
177305
176989
175025
175345
179269
178638
179269
179269
183545
184176
172398
172398
176989
174709
170785
172398
176327
174363
174047
169803
176007
177305
164545
164229
170785
167176
160967
163598
166509
167176
165212
161287
169456
169456
155078
154101
158025
150838
143616
145932
150838
146910
144283
138710
146247
146563
132190
131839
134470
126301
117465
121043
125950
120728
120412
115154
123670
125319
109266
105688
107968
99132
89981
92928
98470
91946
92928
89004
97172
98150
78524
77221
80799
71333
62817
65764
72950
64462
63799
57244
64462
66742
46448
46448
49391
41542
32706
37297
45466
36631
40244
35333
43186
45813
24853
23240
26502
18649
12444
15040

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'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169336&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169336&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169336&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'Gwilym Jenkins' @ jenkins.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0114691.14091083453478.86059761727
0.0218366.90949892824667.09497635454
0.0322226.42074595365262.98178255684
0.0425891.16163121335676.88062786997
0.0529311.70713767285897.14918643393
0.0632455.62716028175764.00007520949
0.0735276.37443385195424.0817312942
0.0837781.60106790555148.56266356129
0.0940051.64482461985100.04523249774
0.142205.41513302565330.85127259882
0.1144364.07741603075849.88279468903
0.1246628.90549884836610.4794161087
0.1349064.68710135847479.39186730868
0.1451686.77039125058271.98673070394
0.1554460.79525165688836.79591193975
0.1657320.96207015059127.1562361037
0.1760200.18877502099217.59771763502
0.1863056.99580715789257.07276750495
0.1965886.32654124129386.57195959742
0.268711.61501091949668.5384304468
0.2171565.357489173410069.1972060433
0.2274469.45833114610492.8858893426
0.2377424.112728297310836.3399673306
0.2480408.135984457311030.5667563732
0.2583388.213673721311060.4188679153
0.2686331.690962752610964.4751812106
0.2789217.469660443910815.1759243726
0.2892041.423472587110693.4301667549
0.2994815.302267654410659.3111027651
0.397560.422834943510732.9664442653
0.31100298.93314050310890.9430332402
0.32103045.82832577811079.2740887465
0.33105804.24770342311233.3903904064
0.34108565.22310090911303.3094360348
0.35111311.47826362111265.9443581892
0.36114023.60834955811131.41309597
0.37116686.36705488310937.0671780593
0.38119292.98052667310733.7767409376
0.39121846.25319319210568.3823584627
0.4124356.39706381110468.4845083489
0.41126836.59721785510433.7160507357
0.42129297.97941543810438.4323610406
0.43131745.69429353410441.9705026422
0.44134177.30847147410404.6356577179
0.45136583.81214430910299.3452882846
0.46138952.63543625610119.2224674333
0.47141271.426445829878.38645114685
0.48143531.1861816889602.58466029474
0.49145727.7051117089321.02386346806
0.5147860.9463020919052.84423139812
0.51149932.7952929148801.13444083245
0.52151944.1594638378552.36152599603
0.53153892.5602652518282.85347754691
0.54155771.0955869767968.58395398027
0.55157569.0938642637593.02981948227
0.56159274.1680291847153.97510447676
0.57160874.9334841126663.28697936453
0.58162363.5161588426143.78868225966
0.59163737.1492975745622.67134783222
0.6164998.5314694085126.10896747081
0.61166155.0295215824673.11971123558
0.62167217.1126756554273.64171621028
0.63168196.522189263929.09004233535
0.64169104.6242725543633.71677224429
0.65169951.2321548193377.95053942353
0.66170744.0018207073151.03012663336
0.67171488.365299462943.03577417173
0.68172187.883495092746.75195403167
0.69172844.8633215532557.95822710604
0.7173461.0704057612375.59879502631
0.71174038.3711958452201.3825477584
0.72174579.1640183092038.70624987193
0.73175086.5139833491890.45927147374
0.74175563.9820566761758.99744069052
0.75176015.2094155281643.67300988931
0.76176443.3636608651541.61718065304
0.77176850.5758193291447.91350907967
0.78177237.5178339861356.79814562207
0.79177603.3003292291262.13478686536
0.8177945.8803334951159.52683875588
0.81178263.0945314681048.82809925164
0.82178554.228607981936.203052489245
0.83178821.72808128833.786297699644
0.84179072.375071137758.301963360762
0.85179317.168473457724.574968295749
0.86179569.394152733738.050545790806
0.87179841.026456621787.006284507736
0.88180138.625430631845.321957637818
0.89180461.023723882883.462847224035
0.9180801.628848304883.705207314677
0.91181156.932214055857.814975730243
0.92181538.952284259856.338170486564
0.93181984.076203763948.53056220221
0.94182548.6859436351156.8324244442
0.95183287.5087636871418.29426399828
0.96184219.0617436431619.09079134963
0.97185284.0524858631620.23344991533
0.98186317.7198558551272.78484438496
0.99187100.279346634656.469180927451

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 14691.1409108345 & 3478.86059761727 \tabularnewline
0.02 & 18366.9094989282 & 4667.09497635454 \tabularnewline
0.03 & 22226.4207459536 & 5262.98178255684 \tabularnewline
0.04 & 25891.1616312133 & 5676.88062786997 \tabularnewline
0.05 & 29311.7071376728 & 5897.14918643393 \tabularnewline
0.06 & 32455.6271602817 & 5764.00007520949 \tabularnewline
0.07 & 35276.3744338519 & 5424.0817312942 \tabularnewline
0.08 & 37781.6010679055 & 5148.56266356129 \tabularnewline
0.09 & 40051.6448246198 & 5100.04523249774 \tabularnewline
0.1 & 42205.4151330256 & 5330.85127259882 \tabularnewline
0.11 & 44364.0774160307 & 5849.88279468903 \tabularnewline
0.12 & 46628.9054988483 & 6610.4794161087 \tabularnewline
0.13 & 49064.6871013584 & 7479.39186730868 \tabularnewline
0.14 & 51686.7703912505 & 8271.98673070394 \tabularnewline
0.15 & 54460.7952516568 & 8836.79591193975 \tabularnewline
0.16 & 57320.9620701505 & 9127.1562361037 \tabularnewline
0.17 & 60200.1887750209 & 9217.59771763502 \tabularnewline
0.18 & 63056.9958071578 & 9257.07276750495 \tabularnewline
0.19 & 65886.3265412412 & 9386.57195959742 \tabularnewline
0.2 & 68711.6150109194 & 9668.5384304468 \tabularnewline
0.21 & 71565.3574891734 & 10069.1972060433 \tabularnewline
0.22 & 74469.458331146 & 10492.8858893426 \tabularnewline
0.23 & 77424.1127282973 & 10836.3399673306 \tabularnewline
0.24 & 80408.1359844573 & 11030.5667563732 \tabularnewline
0.25 & 83388.2136737213 & 11060.4188679153 \tabularnewline
0.26 & 86331.6909627526 & 10964.4751812106 \tabularnewline
0.27 & 89217.4696604439 & 10815.1759243726 \tabularnewline
0.28 & 92041.4234725871 & 10693.4301667549 \tabularnewline
0.29 & 94815.3022676544 & 10659.3111027651 \tabularnewline
0.3 & 97560.4228349435 & 10732.9664442653 \tabularnewline
0.31 & 100298.933140503 & 10890.9430332402 \tabularnewline
0.32 & 103045.828325778 & 11079.2740887465 \tabularnewline
0.33 & 105804.247703423 & 11233.3903904064 \tabularnewline
0.34 & 108565.223100909 & 11303.3094360348 \tabularnewline
0.35 & 111311.478263621 & 11265.9443581892 \tabularnewline
0.36 & 114023.608349558 & 11131.41309597 \tabularnewline
0.37 & 116686.367054883 & 10937.0671780593 \tabularnewline
0.38 & 119292.980526673 & 10733.7767409376 \tabularnewline
0.39 & 121846.253193192 & 10568.3823584627 \tabularnewline
0.4 & 124356.397063811 & 10468.4845083489 \tabularnewline
0.41 & 126836.597217855 & 10433.7160507357 \tabularnewline
0.42 & 129297.979415438 & 10438.4323610406 \tabularnewline
0.43 & 131745.694293534 & 10441.9705026422 \tabularnewline
0.44 & 134177.308471474 & 10404.6356577179 \tabularnewline
0.45 & 136583.812144309 & 10299.3452882846 \tabularnewline
0.46 & 138952.635436256 & 10119.2224674333 \tabularnewline
0.47 & 141271.42644582 & 9878.38645114685 \tabularnewline
0.48 & 143531.186181688 & 9602.58466029474 \tabularnewline
0.49 & 145727.705111708 & 9321.02386346806 \tabularnewline
0.5 & 147860.946302091 & 9052.84423139812 \tabularnewline
0.51 & 149932.795292914 & 8801.13444083245 \tabularnewline
0.52 & 151944.159463837 & 8552.36152599603 \tabularnewline
0.53 & 153892.560265251 & 8282.85347754691 \tabularnewline
0.54 & 155771.095586976 & 7968.58395398027 \tabularnewline
0.55 & 157569.093864263 & 7593.02981948227 \tabularnewline
0.56 & 159274.168029184 & 7153.97510447676 \tabularnewline
0.57 & 160874.933484112 & 6663.28697936453 \tabularnewline
0.58 & 162363.516158842 & 6143.78868225966 \tabularnewline
0.59 & 163737.149297574 & 5622.67134783222 \tabularnewline
0.6 & 164998.531469408 & 5126.10896747081 \tabularnewline
0.61 & 166155.029521582 & 4673.11971123558 \tabularnewline
0.62 & 167217.112675655 & 4273.64171621028 \tabularnewline
0.63 & 168196.52218926 & 3929.09004233535 \tabularnewline
0.64 & 169104.624272554 & 3633.71677224429 \tabularnewline
0.65 & 169951.232154819 & 3377.95053942353 \tabularnewline
0.66 & 170744.001820707 & 3151.03012663336 \tabularnewline
0.67 & 171488.36529946 & 2943.03577417173 \tabularnewline
0.68 & 172187.88349509 & 2746.75195403167 \tabularnewline
0.69 & 172844.863321553 & 2557.95822710604 \tabularnewline
0.7 & 173461.070405761 & 2375.59879502631 \tabularnewline
0.71 & 174038.371195845 & 2201.3825477584 \tabularnewline
0.72 & 174579.164018309 & 2038.70624987193 \tabularnewline
0.73 & 175086.513983349 & 1890.45927147374 \tabularnewline
0.74 & 175563.982056676 & 1758.99744069052 \tabularnewline
0.75 & 176015.209415528 & 1643.67300988931 \tabularnewline
0.76 & 176443.363660865 & 1541.61718065304 \tabularnewline
0.77 & 176850.575819329 & 1447.91350907967 \tabularnewline
0.78 & 177237.517833986 & 1356.79814562207 \tabularnewline
0.79 & 177603.300329229 & 1262.13478686536 \tabularnewline
0.8 & 177945.880333495 & 1159.52683875588 \tabularnewline
0.81 & 178263.094531468 & 1048.82809925164 \tabularnewline
0.82 & 178554.228607981 & 936.203052489245 \tabularnewline
0.83 & 178821.72808128 & 833.786297699644 \tabularnewline
0.84 & 179072.375071137 & 758.301963360762 \tabularnewline
0.85 & 179317.168473457 & 724.574968295749 \tabularnewline
0.86 & 179569.394152733 & 738.050545790806 \tabularnewline
0.87 & 179841.026456621 & 787.006284507736 \tabularnewline
0.88 & 180138.625430631 & 845.321957637818 \tabularnewline
0.89 & 180461.023723882 & 883.462847224035 \tabularnewline
0.9 & 180801.628848304 & 883.705207314677 \tabularnewline
0.91 & 181156.932214055 & 857.814975730243 \tabularnewline
0.92 & 181538.952284259 & 856.338170486564 \tabularnewline
0.93 & 181984.076203763 & 948.53056220221 \tabularnewline
0.94 & 182548.685943635 & 1156.8324244442 \tabularnewline
0.95 & 183287.508763687 & 1418.29426399828 \tabularnewline
0.96 & 184219.061743643 & 1619.09079134963 \tabularnewline
0.97 & 185284.052485863 & 1620.23344991533 \tabularnewline
0.98 & 186317.719855855 & 1272.78484438496 \tabularnewline
0.99 & 187100.279346634 & 656.469180927451 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169336&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]14691.1409108345[/C][C]3478.86059761727[/C][/ROW]
[ROW][C]0.02[/C][C]18366.9094989282[/C][C]4667.09497635454[/C][/ROW]
[ROW][C]0.03[/C][C]22226.4207459536[/C][C]5262.98178255684[/C][/ROW]
[ROW][C]0.04[/C][C]25891.1616312133[/C][C]5676.88062786997[/C][/ROW]
[ROW][C]0.05[/C][C]29311.7071376728[/C][C]5897.14918643393[/C][/ROW]
[ROW][C]0.06[/C][C]32455.6271602817[/C][C]5764.00007520949[/C][/ROW]
[ROW][C]0.07[/C][C]35276.3744338519[/C][C]5424.0817312942[/C][/ROW]
[ROW][C]0.08[/C][C]37781.6010679055[/C][C]5148.56266356129[/C][/ROW]
[ROW][C]0.09[/C][C]40051.6448246198[/C][C]5100.04523249774[/C][/ROW]
[ROW][C]0.1[/C][C]42205.4151330256[/C][C]5330.85127259882[/C][/ROW]
[ROW][C]0.11[/C][C]44364.0774160307[/C][C]5849.88279468903[/C][/ROW]
[ROW][C]0.12[/C][C]46628.9054988483[/C][C]6610.4794161087[/C][/ROW]
[ROW][C]0.13[/C][C]49064.6871013584[/C][C]7479.39186730868[/C][/ROW]
[ROW][C]0.14[/C][C]51686.7703912505[/C][C]8271.98673070394[/C][/ROW]
[ROW][C]0.15[/C][C]54460.7952516568[/C][C]8836.79591193975[/C][/ROW]
[ROW][C]0.16[/C][C]57320.9620701505[/C][C]9127.1562361037[/C][/ROW]
[ROW][C]0.17[/C][C]60200.1887750209[/C][C]9217.59771763502[/C][/ROW]
[ROW][C]0.18[/C][C]63056.9958071578[/C][C]9257.07276750495[/C][/ROW]
[ROW][C]0.19[/C][C]65886.3265412412[/C][C]9386.57195959742[/C][/ROW]
[ROW][C]0.2[/C][C]68711.6150109194[/C][C]9668.5384304468[/C][/ROW]
[ROW][C]0.21[/C][C]71565.3574891734[/C][C]10069.1972060433[/C][/ROW]
[ROW][C]0.22[/C][C]74469.458331146[/C][C]10492.8858893426[/C][/ROW]
[ROW][C]0.23[/C][C]77424.1127282973[/C][C]10836.3399673306[/C][/ROW]
[ROW][C]0.24[/C][C]80408.1359844573[/C][C]11030.5667563732[/C][/ROW]
[ROW][C]0.25[/C][C]83388.2136737213[/C][C]11060.4188679153[/C][/ROW]
[ROW][C]0.26[/C][C]86331.6909627526[/C][C]10964.4751812106[/C][/ROW]
[ROW][C]0.27[/C][C]89217.4696604439[/C][C]10815.1759243726[/C][/ROW]
[ROW][C]0.28[/C][C]92041.4234725871[/C][C]10693.4301667549[/C][/ROW]
[ROW][C]0.29[/C][C]94815.3022676544[/C][C]10659.3111027651[/C][/ROW]
[ROW][C]0.3[/C][C]97560.4228349435[/C][C]10732.9664442653[/C][/ROW]
[ROW][C]0.31[/C][C]100298.933140503[/C][C]10890.9430332402[/C][/ROW]
[ROW][C]0.32[/C][C]103045.828325778[/C][C]11079.2740887465[/C][/ROW]
[ROW][C]0.33[/C][C]105804.247703423[/C][C]11233.3903904064[/C][/ROW]
[ROW][C]0.34[/C][C]108565.223100909[/C][C]11303.3094360348[/C][/ROW]
[ROW][C]0.35[/C][C]111311.478263621[/C][C]11265.9443581892[/C][/ROW]
[ROW][C]0.36[/C][C]114023.608349558[/C][C]11131.41309597[/C][/ROW]
[ROW][C]0.37[/C][C]116686.367054883[/C][C]10937.0671780593[/C][/ROW]
[ROW][C]0.38[/C][C]119292.980526673[/C][C]10733.7767409376[/C][/ROW]
[ROW][C]0.39[/C][C]121846.253193192[/C][C]10568.3823584627[/C][/ROW]
[ROW][C]0.4[/C][C]124356.397063811[/C][C]10468.4845083489[/C][/ROW]
[ROW][C]0.41[/C][C]126836.597217855[/C][C]10433.7160507357[/C][/ROW]
[ROW][C]0.42[/C][C]129297.979415438[/C][C]10438.4323610406[/C][/ROW]
[ROW][C]0.43[/C][C]131745.694293534[/C][C]10441.9705026422[/C][/ROW]
[ROW][C]0.44[/C][C]134177.308471474[/C][C]10404.6356577179[/C][/ROW]
[ROW][C]0.45[/C][C]136583.812144309[/C][C]10299.3452882846[/C][/ROW]
[ROW][C]0.46[/C][C]138952.635436256[/C][C]10119.2224674333[/C][/ROW]
[ROW][C]0.47[/C][C]141271.42644582[/C][C]9878.38645114685[/C][/ROW]
[ROW][C]0.48[/C][C]143531.186181688[/C][C]9602.58466029474[/C][/ROW]
[ROW][C]0.49[/C][C]145727.705111708[/C][C]9321.02386346806[/C][/ROW]
[ROW][C]0.5[/C][C]147860.946302091[/C][C]9052.84423139812[/C][/ROW]
[ROW][C]0.51[/C][C]149932.795292914[/C][C]8801.13444083245[/C][/ROW]
[ROW][C]0.52[/C][C]151944.159463837[/C][C]8552.36152599603[/C][/ROW]
[ROW][C]0.53[/C][C]153892.560265251[/C][C]8282.85347754691[/C][/ROW]
[ROW][C]0.54[/C][C]155771.095586976[/C][C]7968.58395398027[/C][/ROW]
[ROW][C]0.55[/C][C]157569.093864263[/C][C]7593.02981948227[/C][/ROW]
[ROW][C]0.56[/C][C]159274.168029184[/C][C]7153.97510447676[/C][/ROW]
[ROW][C]0.57[/C][C]160874.933484112[/C][C]6663.28697936453[/C][/ROW]
[ROW][C]0.58[/C][C]162363.516158842[/C][C]6143.78868225966[/C][/ROW]
[ROW][C]0.59[/C][C]163737.149297574[/C][C]5622.67134783222[/C][/ROW]
[ROW][C]0.6[/C][C]164998.531469408[/C][C]5126.10896747081[/C][/ROW]
[ROW][C]0.61[/C][C]166155.029521582[/C][C]4673.11971123558[/C][/ROW]
[ROW][C]0.62[/C][C]167217.112675655[/C][C]4273.64171621028[/C][/ROW]
[ROW][C]0.63[/C][C]168196.52218926[/C][C]3929.09004233535[/C][/ROW]
[ROW][C]0.64[/C][C]169104.624272554[/C][C]3633.71677224429[/C][/ROW]
[ROW][C]0.65[/C][C]169951.232154819[/C][C]3377.95053942353[/C][/ROW]
[ROW][C]0.66[/C][C]170744.001820707[/C][C]3151.03012663336[/C][/ROW]
[ROW][C]0.67[/C][C]171488.36529946[/C][C]2943.03577417173[/C][/ROW]
[ROW][C]0.68[/C][C]172187.88349509[/C][C]2746.75195403167[/C][/ROW]
[ROW][C]0.69[/C][C]172844.863321553[/C][C]2557.95822710604[/C][/ROW]
[ROW][C]0.7[/C][C]173461.070405761[/C][C]2375.59879502631[/C][/ROW]
[ROW][C]0.71[/C][C]174038.371195845[/C][C]2201.3825477584[/C][/ROW]
[ROW][C]0.72[/C][C]174579.164018309[/C][C]2038.70624987193[/C][/ROW]
[ROW][C]0.73[/C][C]175086.513983349[/C][C]1890.45927147374[/C][/ROW]
[ROW][C]0.74[/C][C]175563.982056676[/C][C]1758.99744069052[/C][/ROW]
[ROW][C]0.75[/C][C]176015.209415528[/C][C]1643.67300988931[/C][/ROW]
[ROW][C]0.76[/C][C]176443.363660865[/C][C]1541.61718065304[/C][/ROW]
[ROW][C]0.77[/C][C]176850.575819329[/C][C]1447.91350907967[/C][/ROW]
[ROW][C]0.78[/C][C]177237.517833986[/C][C]1356.79814562207[/C][/ROW]
[ROW][C]0.79[/C][C]177603.300329229[/C][C]1262.13478686536[/C][/ROW]
[ROW][C]0.8[/C][C]177945.880333495[/C][C]1159.52683875588[/C][/ROW]
[ROW][C]0.81[/C][C]178263.094531468[/C][C]1048.82809925164[/C][/ROW]
[ROW][C]0.82[/C][C]178554.228607981[/C][C]936.203052489245[/C][/ROW]
[ROW][C]0.83[/C][C]178821.72808128[/C][C]833.786297699644[/C][/ROW]
[ROW][C]0.84[/C][C]179072.375071137[/C][C]758.301963360762[/C][/ROW]
[ROW][C]0.85[/C][C]179317.168473457[/C][C]724.574968295749[/C][/ROW]
[ROW][C]0.86[/C][C]179569.394152733[/C][C]738.050545790806[/C][/ROW]
[ROW][C]0.87[/C][C]179841.026456621[/C][C]787.006284507736[/C][/ROW]
[ROW][C]0.88[/C][C]180138.625430631[/C][C]845.321957637818[/C][/ROW]
[ROW][C]0.89[/C][C]180461.023723882[/C][C]883.462847224035[/C][/ROW]
[ROW][C]0.9[/C][C]180801.628848304[/C][C]883.705207314677[/C][/ROW]
[ROW][C]0.91[/C][C]181156.932214055[/C][C]857.814975730243[/C][/ROW]
[ROW][C]0.92[/C][C]181538.952284259[/C][C]856.338170486564[/C][/ROW]
[ROW][C]0.93[/C][C]181984.076203763[/C][C]948.53056220221[/C][/ROW]
[ROW][C]0.94[/C][C]182548.685943635[/C][C]1156.8324244442[/C][/ROW]
[ROW][C]0.95[/C][C]183287.508763687[/C][C]1418.29426399828[/C][/ROW]
[ROW][C]0.96[/C][C]184219.061743643[/C][C]1619.09079134963[/C][/ROW]
[ROW][C]0.97[/C][C]185284.052485863[/C][C]1620.23344991533[/C][/ROW]
[ROW][C]0.98[/C][C]186317.719855855[/C][C]1272.78484438496[/C][/ROW]
[ROW][C]0.99[/C][C]187100.279346634[/C][C]656.469180927451[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169336&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169336&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
0.0114691.14091083453478.86059761727
0.0218366.90949892824667.09497635454
0.0322226.42074595365262.98178255684
0.0425891.16163121335676.88062786997
0.0529311.70713767285897.14918643393
0.0632455.62716028175764.00007520949
0.0735276.37443385195424.0817312942
0.0837781.60106790555148.56266356129
0.0940051.64482461985100.04523249774
0.142205.41513302565330.85127259882
0.1144364.07741603075849.88279468903
0.1246628.90549884836610.4794161087
0.1349064.68710135847479.39186730868
0.1451686.77039125058271.98673070394
0.1554460.79525165688836.79591193975
0.1657320.96207015059127.1562361037
0.1760200.18877502099217.59771763502
0.1863056.99580715789257.07276750495
0.1965886.32654124129386.57195959742
0.268711.61501091949668.5384304468
0.2171565.357489173410069.1972060433
0.2274469.45833114610492.8858893426
0.2377424.112728297310836.3399673306
0.2480408.135984457311030.5667563732
0.2583388.213673721311060.4188679153
0.2686331.690962752610964.4751812106
0.2789217.469660443910815.1759243726
0.2892041.423472587110693.4301667549
0.2994815.302267654410659.3111027651
0.397560.422834943510732.9664442653
0.31100298.93314050310890.9430332402
0.32103045.82832577811079.2740887465
0.33105804.24770342311233.3903904064
0.34108565.22310090911303.3094360348
0.35111311.47826362111265.9443581892
0.36114023.60834955811131.41309597
0.37116686.36705488310937.0671780593
0.38119292.98052667310733.7767409376
0.39121846.25319319210568.3823584627
0.4124356.39706381110468.4845083489
0.41126836.59721785510433.7160507357
0.42129297.97941543810438.4323610406
0.43131745.69429353410441.9705026422
0.44134177.30847147410404.6356577179
0.45136583.81214430910299.3452882846
0.46138952.63543625610119.2224674333
0.47141271.426445829878.38645114685
0.48143531.1861816889602.58466029474
0.49145727.7051117089321.02386346806
0.5147860.9463020919052.84423139812
0.51149932.7952929148801.13444083245
0.52151944.1594638378552.36152599603
0.53153892.5602652518282.85347754691
0.54155771.0955869767968.58395398027
0.55157569.0938642637593.02981948227
0.56159274.1680291847153.97510447676
0.57160874.9334841126663.28697936453
0.58162363.5161588426143.78868225966
0.59163737.1492975745622.67134783222
0.6164998.5314694085126.10896747081
0.61166155.0295215824673.11971123558
0.62167217.1126756554273.64171621028
0.63168196.522189263929.09004233535
0.64169104.6242725543633.71677224429
0.65169951.2321548193377.95053942353
0.66170744.0018207073151.03012663336
0.67171488.365299462943.03577417173
0.68172187.883495092746.75195403167
0.69172844.8633215532557.95822710604
0.7173461.0704057612375.59879502631
0.71174038.3711958452201.3825477584
0.72174579.1640183092038.70624987193
0.73175086.5139833491890.45927147374
0.74175563.9820566761758.99744069052
0.75176015.2094155281643.67300988931
0.76176443.3636608651541.61718065304
0.77176850.5758193291447.91350907967
0.78177237.5178339861356.79814562207
0.79177603.3003292291262.13478686536
0.8177945.8803334951159.52683875588
0.81178263.0945314681048.82809925164
0.82178554.228607981936.203052489245
0.83178821.72808128833.786297699644
0.84179072.375071137758.301963360762
0.85179317.168473457724.574968295749
0.86179569.394152733738.050545790806
0.87179841.026456621787.006284507736
0.88180138.625430631845.321957637818
0.89180461.023723882883.462847224035
0.9180801.628848304883.705207314677
0.91181156.932214055857.814975730243
0.92181538.952284259856.338170486564
0.93181984.076203763948.53056220221
0.94182548.6859436351156.8324244442
0.95183287.5087636871418.29426399828
0.96184219.0617436431619.09079134963
0.97185284.0524858631620.23344991533
0.98186317.7198558551272.78484438496
0.99187100.279346634656.469180927451


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.1 ; par2 = 0.9 ; par3 = 0.1 ;
Parameters (R input):
par1 = 0.01 ; par2 = 0.99 ; par3 = 0.01 ;
R code (references can be found in the software module):
par3 <- '0.1'
par2 <- '0.9'
par1 <- '0.1'
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')