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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationTue, 09 Mar 2010 10:55:14 -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/t12681573993b8onbhsir7cx96.htm/, Retrieved Wed, 19 Jan 2022 11:01:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=74205, Retrieved Wed, 19 Jan 2022 11:01:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP1W42
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Harrell-Davis Quantiles] [Melino Olivini - ...] [2010-03-09 17:55:14] [2156736b6f7843cba1ea73b621b47743] [Current]
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Dataseries X:
5221,3
5115,9
5107,4
5202,1
5307,5
5266,1
5329,8
5263,4
5177,1
5204,9
5185,2
5189,8
5253,8
5372,3
5478,4
5590,5
5699,8
5797,9
5854,3
5902,4
5956,9
6007,8
6101,7
6148,6
6207,4
6232
6291,7
6323,4
6365
6435
6493,4
6606,8
6639,1
6723,5
6759,4
6848,6
6918,1
6963,5
7013,1
7030,9
7112,1
7130,3
7130,8
7076,9
7040,8
7086,5
7120,7
7154,1
7228,2
7297,9
7369,5
7450,7
7459,7
7497,5
7536
7637,4
7715,1
7815,7
7859,5
7951,6
7973,7
7988
8053,1
8112
8169,2
8303,1
8372,7
8470,6
8536,1
8665,8
8773,7
8838,4
8936,2
8995,3
9098,9
9237,1
9315,5
9392,6
9502,2
9671,1
9695,6
9847,9
9836,6
9887,7
9875,6
9905,9
9871,1
9910
9977,3
10031,6
10090,7
10095,8
10126
10212,7
10398,7
10467
10543,6
10634,2
10728,7
10796,4
10875,8
10946,1
11050
11086,1
11217,3
11291,7
11314,1
11356,4
11357,8
11491,4
11625,7
11620,7
11646
11700,6




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=74205&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=74205&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74205&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
0.015122.0703819136627.7968344132269
0.025148.1033577474234.1372866035634
0.035172.4936048802827.0669779939451
0.045191.1043000142224.4369107327073
0.055207.039453733730.0071376285232
0.065224.24983133640.8992907386321
0.075245.4543038333956.701584338051
0.085272.7165954186978.845199430817
0.095308.02436523458108.058676940518
0.15353.1223483133142.738053809022
0.115408.89598171258178.883665945513
0.125474.84315104187211.467098595042
0.135549.01259285801236.210941640078
0.145628.45987978651251.030478849658
0.155709.990100793256.345510523067
0.165790.85995726729254.495013585880
0.175869.20300522358248.597229746765
0.185944.11957524698241.508002045082
0.196015.52042325646235.258511523629
0.26083.8671679375231.090454915936
0.216149.92147319586229.617328766105
0.226214.54934316696231.007368802013
0.236278.57578735882235.004488167344
0.246342.66899945587240.901397099195
0.256407.24405475814247.532018249544
0.266472.3937605416253.454874284749
0.276537.86292211607257.236012956604
0.286603.07777402499257.677992644365
0.296667.2297603475254.044645558088
0.36729.40000772687246.155861051216
0.316788.70296627185234.429398267559
0.326844.42595960688219.86091940437
0.336896.14420342997203.845449884702
0.346943.79604400793188.055756423413
0.356987.70931456986174.272500228119
0.367028.57629509686164.114398207651
0.377067.38160820036158.853224565000
0.387105.29403157316159.205711022640
0.397143.5386853079165.076776820491
0.47183.26908548963175.787536658561
0.417225.45807458546190.154929233340
0.427270.82236484413206.759950340983
0.437319.78825257665224.281451721565
0.447372.49793991261241.513503923872
0.457428.84919602085257.56254143736
0.467488.55754093193271.82541471798
0.477551.23002672785284.01080813064
0.487616.44174678398294.158318049623
0.497683.80837293423302.565500544459
0.57753.0487540391309.832993477283
0.517824.03085532381316.732319276331
0.527896.79357456522324.117106530129
0.537971.53831057371332.745363510503
0.548048.5887866583343.083119901027
0.558128.32486803725355.202203503151
0.568211.10344711381368.719654900855
0.578297.18369837857382.967164762467
0.588386.67283092124397.023073699722
0.598479.50172829758410.022787556527
0.68575.42975542893421.26860277364
0.618674.0682397958430.240634341264
0.628774.9064640749436.541555714497
0.638877.32482491963439.861577329235
0.648980.58724416098439.821660544619
0.659083.81672850895435.859762821358
0.669185.97017490472427.27163790713
0.679285.83649228637413.345603393475
0.689382.08200274186393.686201605395
0.699473.35722675097368.390259383349
0.79558.46114412583338.294344965764
0.719636.53793728254305.143490981534
0.729707.2644902032271.36931811829
0.739770.98167510403239.927762249337
0.749828.73219763283213.740873869337
0.759882.18985628708195.356192166762
0.769933.49106105432186.363385702352
0.779984.99899658982187.109656942909
0.7810039.0375851588196.503417693959
0.7910097.6283347632212.489337036305
0.810162.2571024216232.267170391303
0.8110233.6982004955252.717328675738
0.8210311.9295953860270.746487459043
0.8310396.173518161283.815974797429
0.8410485.0769915693290.360097323784
0.8510577.0027173779290.144002554283
0.8610670.3474575330284.093133192332
0.8710763.7713383737273.827576872298
0.8810856.2366313083260.832852946805
0.8910946.8370240244245.660188399603
0.911034.5464983116227.830136552799
0.9111118.1809233011206.539941690653
0.9211196.8949668341182.438086924474
0.9311271.1815961789159.462555858120
0.9411343.4972242906144.022775179988
0.9511416.9372778170138.089710329276
0.9611491.5273689083130.882435929605
0.9711561.687219502106.769842252748
0.9811620.902403477568.2616698357496
0.9911669.153786009946.5590104495571

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 5122.07038191366 & 27.7968344132269 \tabularnewline
0.02 & 5148.10335774742 & 34.1372866035634 \tabularnewline
0.03 & 5172.49360488028 & 27.0669779939451 \tabularnewline
0.04 & 5191.10430001422 & 24.4369107327073 \tabularnewline
0.05 & 5207.0394537337 & 30.0071376285232 \tabularnewline
0.06 & 5224.249831336 & 40.8992907386321 \tabularnewline
0.07 & 5245.45430383339 & 56.701584338051 \tabularnewline
0.08 & 5272.71659541869 & 78.845199430817 \tabularnewline
0.09 & 5308.02436523458 & 108.058676940518 \tabularnewline
0.1 & 5353.1223483133 & 142.738053809022 \tabularnewline
0.11 & 5408.89598171258 & 178.883665945513 \tabularnewline
0.12 & 5474.84315104187 & 211.467098595042 \tabularnewline
0.13 & 5549.01259285801 & 236.210941640078 \tabularnewline
0.14 & 5628.45987978651 & 251.030478849658 \tabularnewline
0.15 & 5709.990100793 & 256.345510523067 \tabularnewline
0.16 & 5790.85995726729 & 254.495013585880 \tabularnewline
0.17 & 5869.20300522358 & 248.597229746765 \tabularnewline
0.18 & 5944.11957524698 & 241.508002045082 \tabularnewline
0.19 & 6015.52042325646 & 235.258511523629 \tabularnewline
0.2 & 6083.8671679375 & 231.090454915936 \tabularnewline
0.21 & 6149.92147319586 & 229.617328766105 \tabularnewline
0.22 & 6214.54934316696 & 231.007368802013 \tabularnewline
0.23 & 6278.57578735882 & 235.004488167344 \tabularnewline
0.24 & 6342.66899945587 & 240.901397099195 \tabularnewline
0.25 & 6407.24405475814 & 247.532018249544 \tabularnewline
0.26 & 6472.3937605416 & 253.454874284749 \tabularnewline
0.27 & 6537.86292211607 & 257.236012956604 \tabularnewline
0.28 & 6603.07777402499 & 257.677992644365 \tabularnewline
0.29 & 6667.2297603475 & 254.044645558088 \tabularnewline
0.3 & 6729.40000772687 & 246.155861051216 \tabularnewline
0.31 & 6788.70296627185 & 234.429398267559 \tabularnewline
0.32 & 6844.42595960688 & 219.86091940437 \tabularnewline
0.33 & 6896.14420342997 & 203.845449884702 \tabularnewline
0.34 & 6943.79604400793 & 188.055756423413 \tabularnewline
0.35 & 6987.70931456986 & 174.272500228119 \tabularnewline
0.36 & 7028.57629509686 & 164.114398207651 \tabularnewline
0.37 & 7067.38160820036 & 158.853224565000 \tabularnewline
0.38 & 7105.29403157316 & 159.205711022640 \tabularnewline
0.39 & 7143.5386853079 & 165.076776820491 \tabularnewline
0.4 & 7183.26908548963 & 175.787536658561 \tabularnewline
0.41 & 7225.45807458546 & 190.154929233340 \tabularnewline
0.42 & 7270.82236484413 & 206.759950340983 \tabularnewline
0.43 & 7319.78825257665 & 224.281451721565 \tabularnewline
0.44 & 7372.49793991261 & 241.513503923872 \tabularnewline
0.45 & 7428.84919602085 & 257.56254143736 \tabularnewline
0.46 & 7488.55754093193 & 271.82541471798 \tabularnewline
0.47 & 7551.23002672785 & 284.01080813064 \tabularnewline
0.48 & 7616.44174678398 & 294.158318049623 \tabularnewline
0.49 & 7683.80837293423 & 302.565500544459 \tabularnewline
0.5 & 7753.0487540391 & 309.832993477283 \tabularnewline
0.51 & 7824.03085532381 & 316.732319276331 \tabularnewline
0.52 & 7896.79357456522 & 324.117106530129 \tabularnewline
0.53 & 7971.53831057371 & 332.745363510503 \tabularnewline
0.54 & 8048.5887866583 & 343.083119901027 \tabularnewline
0.55 & 8128.32486803725 & 355.202203503151 \tabularnewline
0.56 & 8211.10344711381 & 368.719654900855 \tabularnewline
0.57 & 8297.18369837857 & 382.967164762467 \tabularnewline
0.58 & 8386.67283092124 & 397.023073699722 \tabularnewline
0.59 & 8479.50172829758 & 410.022787556527 \tabularnewline
0.6 & 8575.42975542893 & 421.26860277364 \tabularnewline
0.61 & 8674.0682397958 & 430.240634341264 \tabularnewline
0.62 & 8774.9064640749 & 436.541555714497 \tabularnewline
0.63 & 8877.32482491963 & 439.861577329235 \tabularnewline
0.64 & 8980.58724416098 & 439.821660544619 \tabularnewline
0.65 & 9083.81672850895 & 435.859762821358 \tabularnewline
0.66 & 9185.97017490472 & 427.27163790713 \tabularnewline
0.67 & 9285.83649228637 & 413.345603393475 \tabularnewline
0.68 & 9382.08200274186 & 393.686201605395 \tabularnewline
0.69 & 9473.35722675097 & 368.390259383349 \tabularnewline
0.7 & 9558.46114412583 & 338.294344965764 \tabularnewline
0.71 & 9636.53793728254 & 305.143490981534 \tabularnewline
0.72 & 9707.2644902032 & 271.36931811829 \tabularnewline
0.73 & 9770.98167510403 & 239.927762249337 \tabularnewline
0.74 & 9828.73219763283 & 213.740873869337 \tabularnewline
0.75 & 9882.18985628708 & 195.356192166762 \tabularnewline
0.76 & 9933.49106105432 & 186.363385702352 \tabularnewline
0.77 & 9984.99899658982 & 187.109656942909 \tabularnewline
0.78 & 10039.0375851588 & 196.503417693959 \tabularnewline
0.79 & 10097.6283347632 & 212.489337036305 \tabularnewline
0.8 & 10162.2571024216 & 232.267170391303 \tabularnewline
0.81 & 10233.6982004955 & 252.717328675738 \tabularnewline
0.82 & 10311.9295953860 & 270.746487459043 \tabularnewline
0.83 & 10396.173518161 & 283.815974797429 \tabularnewline
0.84 & 10485.0769915693 & 290.360097323784 \tabularnewline
0.85 & 10577.0027173779 & 290.144002554283 \tabularnewline
0.86 & 10670.3474575330 & 284.093133192332 \tabularnewline
0.87 & 10763.7713383737 & 273.827576872298 \tabularnewline
0.88 & 10856.2366313083 & 260.832852946805 \tabularnewline
0.89 & 10946.8370240244 & 245.660188399603 \tabularnewline
0.9 & 11034.5464983116 & 227.830136552799 \tabularnewline
0.91 & 11118.1809233011 & 206.539941690653 \tabularnewline
0.92 & 11196.8949668341 & 182.438086924474 \tabularnewline
0.93 & 11271.1815961789 & 159.462555858120 \tabularnewline
0.94 & 11343.4972242906 & 144.022775179988 \tabularnewline
0.95 & 11416.9372778170 & 138.089710329276 \tabularnewline
0.96 & 11491.5273689083 & 130.882435929605 \tabularnewline
0.97 & 11561.687219502 & 106.769842252748 \tabularnewline
0.98 & 11620.9024034775 & 68.2616698357496 \tabularnewline
0.99 & 11669.1537860099 & 46.5590104495571 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74205&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]5122.07038191366[/C][C]27.7968344132269[/C][/ROW]
[ROW][C]0.02[/C][C]5148.10335774742[/C][C]34.1372866035634[/C][/ROW]
[ROW][C]0.03[/C][C]5172.49360488028[/C][C]27.0669779939451[/C][/ROW]
[ROW][C]0.04[/C][C]5191.10430001422[/C][C]24.4369107327073[/C][/ROW]
[ROW][C]0.05[/C][C]5207.0394537337[/C][C]30.0071376285232[/C][/ROW]
[ROW][C]0.06[/C][C]5224.249831336[/C][C]40.8992907386321[/C][/ROW]
[ROW][C]0.07[/C][C]5245.45430383339[/C][C]56.701584338051[/C][/ROW]
[ROW][C]0.08[/C][C]5272.71659541869[/C][C]78.845199430817[/C][/ROW]
[ROW][C]0.09[/C][C]5308.02436523458[/C][C]108.058676940518[/C][/ROW]
[ROW][C]0.1[/C][C]5353.1223483133[/C][C]142.738053809022[/C][/ROW]
[ROW][C]0.11[/C][C]5408.89598171258[/C][C]178.883665945513[/C][/ROW]
[ROW][C]0.12[/C][C]5474.84315104187[/C][C]211.467098595042[/C][/ROW]
[ROW][C]0.13[/C][C]5549.01259285801[/C][C]236.210941640078[/C][/ROW]
[ROW][C]0.14[/C][C]5628.45987978651[/C][C]251.030478849658[/C][/ROW]
[ROW][C]0.15[/C][C]5709.990100793[/C][C]256.345510523067[/C][/ROW]
[ROW][C]0.16[/C][C]5790.85995726729[/C][C]254.495013585880[/C][/ROW]
[ROW][C]0.17[/C][C]5869.20300522358[/C][C]248.597229746765[/C][/ROW]
[ROW][C]0.18[/C][C]5944.11957524698[/C][C]241.508002045082[/C][/ROW]
[ROW][C]0.19[/C][C]6015.52042325646[/C][C]235.258511523629[/C][/ROW]
[ROW][C]0.2[/C][C]6083.8671679375[/C][C]231.090454915936[/C][/ROW]
[ROW][C]0.21[/C][C]6149.92147319586[/C][C]229.617328766105[/C][/ROW]
[ROW][C]0.22[/C][C]6214.54934316696[/C][C]231.007368802013[/C][/ROW]
[ROW][C]0.23[/C][C]6278.57578735882[/C][C]235.004488167344[/C][/ROW]
[ROW][C]0.24[/C][C]6342.66899945587[/C][C]240.901397099195[/C][/ROW]
[ROW][C]0.25[/C][C]6407.24405475814[/C][C]247.532018249544[/C][/ROW]
[ROW][C]0.26[/C][C]6472.3937605416[/C][C]253.454874284749[/C][/ROW]
[ROW][C]0.27[/C][C]6537.86292211607[/C][C]257.236012956604[/C][/ROW]
[ROW][C]0.28[/C][C]6603.07777402499[/C][C]257.677992644365[/C][/ROW]
[ROW][C]0.29[/C][C]6667.2297603475[/C][C]254.044645558088[/C][/ROW]
[ROW][C]0.3[/C][C]6729.40000772687[/C][C]246.155861051216[/C][/ROW]
[ROW][C]0.31[/C][C]6788.70296627185[/C][C]234.429398267559[/C][/ROW]
[ROW][C]0.32[/C][C]6844.42595960688[/C][C]219.86091940437[/C][/ROW]
[ROW][C]0.33[/C][C]6896.14420342997[/C][C]203.845449884702[/C][/ROW]
[ROW][C]0.34[/C][C]6943.79604400793[/C][C]188.055756423413[/C][/ROW]
[ROW][C]0.35[/C][C]6987.70931456986[/C][C]174.272500228119[/C][/ROW]
[ROW][C]0.36[/C][C]7028.57629509686[/C][C]164.114398207651[/C][/ROW]
[ROW][C]0.37[/C][C]7067.38160820036[/C][C]158.853224565000[/C][/ROW]
[ROW][C]0.38[/C][C]7105.29403157316[/C][C]159.205711022640[/C][/ROW]
[ROW][C]0.39[/C][C]7143.5386853079[/C][C]165.076776820491[/C][/ROW]
[ROW][C]0.4[/C][C]7183.26908548963[/C][C]175.787536658561[/C][/ROW]
[ROW][C]0.41[/C][C]7225.45807458546[/C][C]190.154929233340[/C][/ROW]
[ROW][C]0.42[/C][C]7270.82236484413[/C][C]206.759950340983[/C][/ROW]
[ROW][C]0.43[/C][C]7319.78825257665[/C][C]224.281451721565[/C][/ROW]
[ROW][C]0.44[/C][C]7372.49793991261[/C][C]241.513503923872[/C][/ROW]
[ROW][C]0.45[/C][C]7428.84919602085[/C][C]257.56254143736[/C][/ROW]
[ROW][C]0.46[/C][C]7488.55754093193[/C][C]271.82541471798[/C][/ROW]
[ROW][C]0.47[/C][C]7551.23002672785[/C][C]284.01080813064[/C][/ROW]
[ROW][C]0.48[/C][C]7616.44174678398[/C][C]294.158318049623[/C][/ROW]
[ROW][C]0.49[/C][C]7683.80837293423[/C][C]302.565500544459[/C][/ROW]
[ROW][C]0.5[/C][C]7753.0487540391[/C][C]309.832993477283[/C][/ROW]
[ROW][C]0.51[/C][C]7824.03085532381[/C][C]316.732319276331[/C][/ROW]
[ROW][C]0.52[/C][C]7896.79357456522[/C][C]324.117106530129[/C][/ROW]
[ROW][C]0.53[/C][C]7971.53831057371[/C][C]332.745363510503[/C][/ROW]
[ROW][C]0.54[/C][C]8048.5887866583[/C][C]343.083119901027[/C][/ROW]
[ROW][C]0.55[/C][C]8128.32486803725[/C][C]355.202203503151[/C][/ROW]
[ROW][C]0.56[/C][C]8211.10344711381[/C][C]368.719654900855[/C][/ROW]
[ROW][C]0.57[/C][C]8297.18369837857[/C][C]382.967164762467[/C][/ROW]
[ROW][C]0.58[/C][C]8386.67283092124[/C][C]397.023073699722[/C][/ROW]
[ROW][C]0.59[/C][C]8479.50172829758[/C][C]410.022787556527[/C][/ROW]
[ROW][C]0.6[/C][C]8575.42975542893[/C][C]421.26860277364[/C][/ROW]
[ROW][C]0.61[/C][C]8674.0682397958[/C][C]430.240634341264[/C][/ROW]
[ROW][C]0.62[/C][C]8774.9064640749[/C][C]436.541555714497[/C][/ROW]
[ROW][C]0.63[/C][C]8877.32482491963[/C][C]439.861577329235[/C][/ROW]
[ROW][C]0.64[/C][C]8980.58724416098[/C][C]439.821660544619[/C][/ROW]
[ROW][C]0.65[/C][C]9083.81672850895[/C][C]435.859762821358[/C][/ROW]
[ROW][C]0.66[/C][C]9185.97017490472[/C][C]427.27163790713[/C][/ROW]
[ROW][C]0.67[/C][C]9285.83649228637[/C][C]413.345603393475[/C][/ROW]
[ROW][C]0.68[/C][C]9382.08200274186[/C][C]393.686201605395[/C][/ROW]
[ROW][C]0.69[/C][C]9473.35722675097[/C][C]368.390259383349[/C][/ROW]
[ROW][C]0.7[/C][C]9558.46114412583[/C][C]338.294344965764[/C][/ROW]
[ROW][C]0.71[/C][C]9636.53793728254[/C][C]305.143490981534[/C][/ROW]
[ROW][C]0.72[/C][C]9707.2644902032[/C][C]271.36931811829[/C][/ROW]
[ROW][C]0.73[/C][C]9770.98167510403[/C][C]239.927762249337[/C][/ROW]
[ROW][C]0.74[/C][C]9828.73219763283[/C][C]213.740873869337[/C][/ROW]
[ROW][C]0.75[/C][C]9882.18985628708[/C][C]195.356192166762[/C][/ROW]
[ROW][C]0.76[/C][C]9933.49106105432[/C][C]186.363385702352[/C][/ROW]
[ROW][C]0.77[/C][C]9984.99899658982[/C][C]187.109656942909[/C][/ROW]
[ROW][C]0.78[/C][C]10039.0375851588[/C][C]196.503417693959[/C][/ROW]
[ROW][C]0.79[/C][C]10097.6283347632[/C][C]212.489337036305[/C][/ROW]
[ROW][C]0.8[/C][C]10162.2571024216[/C][C]232.267170391303[/C][/ROW]
[ROW][C]0.81[/C][C]10233.6982004955[/C][C]252.717328675738[/C][/ROW]
[ROW][C]0.82[/C][C]10311.9295953860[/C][C]270.746487459043[/C][/ROW]
[ROW][C]0.83[/C][C]10396.173518161[/C][C]283.815974797429[/C][/ROW]
[ROW][C]0.84[/C][C]10485.0769915693[/C][C]290.360097323784[/C][/ROW]
[ROW][C]0.85[/C][C]10577.0027173779[/C][C]290.144002554283[/C][/ROW]
[ROW][C]0.86[/C][C]10670.3474575330[/C][C]284.093133192332[/C][/ROW]
[ROW][C]0.87[/C][C]10763.7713383737[/C][C]273.827576872298[/C][/ROW]
[ROW][C]0.88[/C][C]10856.2366313083[/C][C]260.832852946805[/C][/ROW]
[ROW][C]0.89[/C][C]10946.8370240244[/C][C]245.660188399603[/C][/ROW]
[ROW][C]0.9[/C][C]11034.5464983116[/C][C]227.830136552799[/C][/ROW]
[ROW][C]0.91[/C][C]11118.1809233011[/C][C]206.539941690653[/C][/ROW]
[ROW][C]0.92[/C][C]11196.8949668341[/C][C]182.438086924474[/C][/ROW]
[ROW][C]0.93[/C][C]11271.1815961789[/C][C]159.462555858120[/C][/ROW]
[ROW][C]0.94[/C][C]11343.4972242906[/C][C]144.022775179988[/C][/ROW]
[ROW][C]0.95[/C][C]11416.9372778170[/C][C]138.089710329276[/C][/ROW]
[ROW][C]0.96[/C][C]11491.5273689083[/C][C]130.882435929605[/C][/ROW]
[ROW][C]0.97[/C][C]11561.687219502[/C][C]106.769842252748[/C][/ROW]
[ROW][C]0.98[/C][C]11620.9024034775[/C][C]68.2616698357496[/C][/ROW]
[ROW][C]0.99[/C][C]11669.1537860099[/C][C]46.5590104495571[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74205&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74205&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
0.015122.0703819136627.7968344132269
0.025148.1033577474234.1372866035634
0.035172.4936048802827.0669779939451
0.045191.1043000142224.4369107327073
0.055207.039453733730.0071376285232
0.065224.24983133640.8992907386321
0.075245.4543038333956.701584338051
0.085272.7165954186978.845199430817
0.095308.02436523458108.058676940518
0.15353.1223483133142.738053809022
0.115408.89598171258178.883665945513
0.125474.84315104187211.467098595042
0.135549.01259285801236.210941640078
0.145628.45987978651251.030478849658
0.155709.990100793256.345510523067
0.165790.85995726729254.495013585880
0.175869.20300522358248.597229746765
0.185944.11957524698241.508002045082
0.196015.52042325646235.258511523629
0.26083.8671679375231.090454915936
0.216149.92147319586229.617328766105
0.226214.54934316696231.007368802013
0.236278.57578735882235.004488167344
0.246342.66899945587240.901397099195
0.256407.24405475814247.532018249544
0.266472.3937605416253.454874284749
0.276537.86292211607257.236012956604
0.286603.07777402499257.677992644365
0.296667.2297603475254.044645558088
0.36729.40000772687246.155861051216
0.316788.70296627185234.429398267559
0.326844.42595960688219.86091940437
0.336896.14420342997203.845449884702
0.346943.79604400793188.055756423413
0.356987.70931456986174.272500228119
0.367028.57629509686164.114398207651
0.377067.38160820036158.853224565000
0.387105.29403157316159.205711022640
0.397143.5386853079165.076776820491
0.47183.26908548963175.787536658561
0.417225.45807458546190.154929233340
0.427270.82236484413206.759950340983
0.437319.78825257665224.281451721565
0.447372.49793991261241.513503923872
0.457428.84919602085257.56254143736
0.467488.55754093193271.82541471798
0.477551.23002672785284.01080813064
0.487616.44174678398294.158318049623
0.497683.80837293423302.565500544459
0.57753.0487540391309.832993477283
0.517824.03085532381316.732319276331
0.527896.79357456522324.117106530129
0.537971.53831057371332.745363510503
0.548048.5887866583343.083119901027
0.558128.32486803725355.202203503151
0.568211.10344711381368.719654900855
0.578297.18369837857382.967164762467
0.588386.67283092124397.023073699722
0.598479.50172829758410.022787556527
0.68575.42975542893421.26860277364
0.618674.0682397958430.240634341264
0.628774.9064640749436.541555714497
0.638877.32482491963439.861577329235
0.648980.58724416098439.821660544619
0.659083.81672850895435.859762821358
0.669185.97017490472427.27163790713
0.679285.83649228637413.345603393475
0.689382.08200274186393.686201605395
0.699473.35722675097368.390259383349
0.79558.46114412583338.294344965764
0.719636.53793728254305.143490981534
0.729707.2644902032271.36931811829
0.739770.98167510403239.927762249337
0.749828.73219763283213.740873869337
0.759882.18985628708195.356192166762
0.769933.49106105432186.363385702352
0.779984.99899658982187.109656942909
0.7810039.0375851588196.503417693959
0.7910097.6283347632212.489337036305
0.810162.2571024216232.267170391303
0.8110233.6982004955252.717328675738
0.8210311.9295953860270.746487459043
0.8310396.173518161283.815974797429
0.8410485.0769915693290.360097323784
0.8510577.0027173779290.144002554283
0.8610670.3474575330284.093133192332
0.8710763.7713383737273.827576872298
0.8810856.2366313083260.832852946805
0.8910946.8370240244245.660188399603
0.911034.5464983116227.830136552799
0.9111118.1809233011206.539941690653
0.9211196.8949668341182.438086924474
0.9311271.1815961789159.462555858120
0.9411343.4972242906144.022775179988
0.9511416.9372778170138.089710329276
0.9611491.5273689083130.882435929605
0.9711561.687219502106.769842252748
0.9811620.902403477568.2616698357496
0.9911669.153786009946.5590104495571



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')