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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationSun, 18 Oct 2009 08:58:47 -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/2009/Oct/18/t1255877987pf9wl7b4r3ywjg3.htm/, Retrieved Mon, 29 Apr 2024 14:42:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=47347, Retrieved Mon, 29 Apr 2024 14:42:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsws3p2b2
Estimated Impact129

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] [] [2009-10-18 14:58:47] [9ea4b07b6662a0f40f92decdf1e3b5d5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5596,22
8148,91
7449,67
6768,80
6962,11
7982,99
9576,28
8449,08
7774,25
9074,05
10227,48
10191,50
10413,21
8309,06
8980,02
10597,72
10028,35
9324,74
6583,41
7450,08
7818,56
6922,01
6179,63
6471,26
5048,99
5081,70
6393,43
7288,01
7474,38
7711,85
8356,11
8360,59
5915,39
5886,06
5757,45
4812,07
6697,20
9195,60
12103,04
11879,47
12874,59
13374,82
16934,95
15774,40
18257,77
17589,08
18007,95
15967,01
12000,10
9508,20
5849,29
5011,23
4201,50
3223,24
1155,95
1231,21
-750,95
-2277,91
-3852,93
-1905,75

Tables (Output of Computation)





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=47347&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=47347&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=47347&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01-3485.219544423431371.49171598565
0.02-2927.212771727211221.80543046011
0.03-2302.807024454081245.69847421367
0.04-1670.206472161241423.7059458641
0.05-1037.174530762821644.05237749834
0.06-398.4881847786891828.43038895629
0.07244.3902683228571947.17168563160
0.08881.4116639220531997.79364221407
0.091498.696667217031987.18340269255
0.12082.867130062881923.12099569924
0.112623.218156743781813.27823103326
0.123112.399174920861667.12743132668
0.133546.480920579431497.00932811755
0.143924.803644849111317.20385386182
0.154249.63941334361141.73822139112
0.164525.61993034268982.116920476027
0.174758.96080748693845.80926246947
0.184956.60672487552735.836365981014
0.195125.45343150264651.238839198401
0.25271.76734812357588.371659683852
0.215400.85378879167542.438099459218
0.225516.95656878964508.883957036208
0.235623.3275105865484.132145268391
0.245722.38987103672465.779187981576
0.255815.92890526705452.297088482552
0.265905.26460191668442.693157138745
0.275991.38552416656436.205057822798
0.286075.04157086193432.124484228292
0.296156.80436012914429.786934632162
0.36237.10722332638428.601603721772
0.316316.2748349796428.126627232274
0.326394.54821578469428.093448247143
0.336472.10668357674428.372084010026
0.346549.08574415402428.953398017992
0.356625.58929657122429.828346739295
0.366701.69545229795430.951009986658
0.376777.456900845432.186727364417
0.386852.89824110624433.310791955179
0.396928.01343661689434.080365110841
0.47002.76631950682434.207461320138
0.417077.09599631271433.500627921387
0.427150.92747830073431.873833123186
0.437224.18633877949429.379221879389
0.447296.81510203605426.211736767662
0.457368.7886431548422.697643540149
0.467440.12616813154419.222508408162
0.477510.89819934833416.180593132162
0.487581.22813001729413.953376336508
0.497651.28900384128412.829598082456
0.57721.29693724092413.0521164666
0.517791.50286002559414.756609279367
0.527862.1839883472418.007315734516
0.537933.63579439817422.879582672516
0.548006.16444441511429.40077580874
0.558080.07902484337437.573595505028
0.568155.68260944082447.376562092808
0.578233.26146579598458.703400567062
0.588313.07242591762471.338029210586
0.598395.32945884295484.972812116816
0.68480.19147813024499.134839253549
0.618567.75406549158513.298920158917
0.628658.0478487429526.936369813005
0.638751.04566425276539.595061073958
0.648846.67949547148550.964383305532
0.658944.8668144252560.958582076477
0.669045.54472808888569.757996331137
0.679148.70952574644577.772670862978
0.689254.45890080733585.659000069094
0.699363.03408469383594.260333837623
0.79474.85901066377604.571427242958
0.719590.57309411706617.722291025906
0.729711.05327133536634.934750130777
0.739837.42012496137657.480229327461
0.749971.02333064443686.484859583161
0.7510113.4045711830722.765965354975
0.7610266.2422620300766.591182786837
0.7710431.2913026962817.540379611355
0.7810610.3399127147874.512143879417
0.7910805.2096420699936.131040098241
0.811017.81814344091001.29500324338
0.8111250.30305070911069.80378638220
0.8211505.16993266721142.87703404510
0.8311785.38614579351223.00425165973
0.8412094.31232000911312.96590539346
0.8512435.36594335781413.92110117953
0.8612811.36503030161523.09399649129
0.8713223.60585445061632.21728145585
0.8813670.86160758141727.60250381325
0.8914148.59461452911792.44425888063
0.914648.68777806231810.77956307521
0.9115159.87942544381771.99098022661
0.9215668.85174314571673.98933633024
0.9316161.67772458941523.62290959147
0.9416625.21252002541333.79806189774
0.9517048.08655306731118.97800347148
0.9617421.0965848904892.150252567762
0.9717736.7513944701666.221369248368
0.9817987.6391542415460.781656842277
0.9918164.3826075062310.441354864667

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & -3485.21954442343 & 1371.49171598565 \tabularnewline
0.02 & -2927.21277172721 & 1221.80543046011 \tabularnewline
0.03 & -2302.80702445408 & 1245.69847421367 \tabularnewline
0.04 & -1670.20647216124 & 1423.7059458641 \tabularnewline
0.05 & -1037.17453076282 & 1644.05237749834 \tabularnewline
0.06 & -398.488184778689 & 1828.43038895629 \tabularnewline
0.07 & 244.390268322857 & 1947.17168563160 \tabularnewline
0.08 & 881.411663922053 & 1997.79364221407 \tabularnewline
0.09 & 1498.69666721703 & 1987.18340269255 \tabularnewline
0.1 & 2082.86713006288 & 1923.12099569924 \tabularnewline
0.11 & 2623.21815674378 & 1813.27823103326 \tabularnewline
0.12 & 3112.39917492086 & 1667.12743132668 \tabularnewline
0.13 & 3546.48092057943 & 1497.00932811755 \tabularnewline
0.14 & 3924.80364484911 & 1317.20385386182 \tabularnewline
0.15 & 4249.6394133436 & 1141.73822139112 \tabularnewline
0.16 & 4525.61993034268 & 982.116920476027 \tabularnewline
0.17 & 4758.96080748693 & 845.80926246947 \tabularnewline
0.18 & 4956.60672487552 & 735.836365981014 \tabularnewline
0.19 & 5125.45343150264 & 651.238839198401 \tabularnewline
0.2 & 5271.76734812357 & 588.371659683852 \tabularnewline
0.21 & 5400.85378879167 & 542.438099459218 \tabularnewline
0.22 & 5516.95656878964 & 508.883957036208 \tabularnewline
0.23 & 5623.3275105865 & 484.132145268391 \tabularnewline
0.24 & 5722.38987103672 & 465.779187981576 \tabularnewline
0.25 & 5815.92890526705 & 452.297088482552 \tabularnewline
0.26 & 5905.26460191668 & 442.693157138745 \tabularnewline
0.27 & 5991.38552416656 & 436.205057822798 \tabularnewline
0.28 & 6075.04157086193 & 432.124484228292 \tabularnewline
0.29 & 6156.80436012914 & 429.786934632162 \tabularnewline
0.3 & 6237.10722332638 & 428.601603721772 \tabularnewline
0.31 & 6316.2748349796 & 428.126627232274 \tabularnewline
0.32 & 6394.54821578469 & 428.093448247143 \tabularnewline
0.33 & 6472.10668357674 & 428.372084010026 \tabularnewline
0.34 & 6549.08574415402 & 428.953398017992 \tabularnewline
0.35 & 6625.58929657122 & 429.828346739295 \tabularnewline
0.36 & 6701.69545229795 & 430.951009986658 \tabularnewline
0.37 & 6777.456900845 & 432.186727364417 \tabularnewline
0.38 & 6852.89824110624 & 433.310791955179 \tabularnewline
0.39 & 6928.01343661689 & 434.080365110841 \tabularnewline
0.4 & 7002.76631950682 & 434.207461320138 \tabularnewline
0.41 & 7077.09599631271 & 433.500627921387 \tabularnewline
0.42 & 7150.92747830073 & 431.873833123186 \tabularnewline
0.43 & 7224.18633877949 & 429.379221879389 \tabularnewline
0.44 & 7296.81510203605 & 426.211736767662 \tabularnewline
0.45 & 7368.7886431548 & 422.697643540149 \tabularnewline
0.46 & 7440.12616813154 & 419.222508408162 \tabularnewline
0.47 & 7510.89819934833 & 416.180593132162 \tabularnewline
0.48 & 7581.22813001729 & 413.953376336508 \tabularnewline
0.49 & 7651.28900384128 & 412.829598082456 \tabularnewline
0.5 & 7721.29693724092 & 413.0521164666 \tabularnewline
0.51 & 7791.50286002559 & 414.756609279367 \tabularnewline
0.52 & 7862.1839883472 & 418.007315734516 \tabularnewline
0.53 & 7933.63579439817 & 422.879582672516 \tabularnewline
0.54 & 8006.16444441511 & 429.40077580874 \tabularnewline
0.55 & 8080.07902484337 & 437.573595505028 \tabularnewline
0.56 & 8155.68260944082 & 447.376562092808 \tabularnewline
0.57 & 8233.26146579598 & 458.703400567062 \tabularnewline
0.58 & 8313.07242591762 & 471.338029210586 \tabularnewline
0.59 & 8395.32945884295 & 484.972812116816 \tabularnewline
0.6 & 8480.19147813024 & 499.134839253549 \tabularnewline
0.61 & 8567.75406549158 & 513.298920158917 \tabularnewline
0.62 & 8658.0478487429 & 526.936369813005 \tabularnewline
0.63 & 8751.04566425276 & 539.595061073958 \tabularnewline
0.64 & 8846.67949547148 & 550.964383305532 \tabularnewline
0.65 & 8944.8668144252 & 560.958582076477 \tabularnewline
0.66 & 9045.54472808888 & 569.757996331137 \tabularnewline
0.67 & 9148.70952574644 & 577.772670862978 \tabularnewline
0.68 & 9254.45890080733 & 585.659000069094 \tabularnewline
0.69 & 9363.03408469383 & 594.260333837623 \tabularnewline
0.7 & 9474.85901066377 & 604.571427242958 \tabularnewline
0.71 & 9590.57309411706 & 617.722291025906 \tabularnewline
0.72 & 9711.05327133536 & 634.934750130777 \tabularnewline
0.73 & 9837.42012496137 & 657.480229327461 \tabularnewline
0.74 & 9971.02333064443 & 686.484859583161 \tabularnewline
0.75 & 10113.4045711830 & 722.765965354975 \tabularnewline
0.76 & 10266.2422620300 & 766.591182786837 \tabularnewline
0.77 & 10431.2913026962 & 817.540379611355 \tabularnewline
0.78 & 10610.3399127147 & 874.512143879417 \tabularnewline
0.79 & 10805.2096420699 & 936.131040098241 \tabularnewline
0.8 & 11017.8181434409 & 1001.29500324338 \tabularnewline
0.81 & 11250.3030507091 & 1069.80378638220 \tabularnewline
0.82 & 11505.1699326672 & 1142.87703404510 \tabularnewline
0.83 & 11785.3861457935 & 1223.00425165973 \tabularnewline
0.84 & 12094.3123200091 & 1312.96590539346 \tabularnewline
0.85 & 12435.3659433578 & 1413.92110117953 \tabularnewline
0.86 & 12811.3650303016 & 1523.09399649129 \tabularnewline
0.87 & 13223.6058544506 & 1632.21728145585 \tabularnewline
0.88 & 13670.8616075814 & 1727.60250381325 \tabularnewline
0.89 & 14148.5946145291 & 1792.44425888063 \tabularnewline
0.9 & 14648.6877780623 & 1810.77956307521 \tabularnewline
0.91 & 15159.8794254438 & 1771.99098022661 \tabularnewline
0.92 & 15668.8517431457 & 1673.98933633024 \tabularnewline
0.93 & 16161.6777245894 & 1523.62290959147 \tabularnewline
0.94 & 16625.2125200254 & 1333.79806189774 \tabularnewline
0.95 & 17048.0865530673 & 1118.97800347148 \tabularnewline
0.96 & 17421.0965848904 & 892.150252567762 \tabularnewline
0.97 & 17736.7513944701 & 666.221369248368 \tabularnewline
0.98 & 17987.6391542415 & 460.781656842277 \tabularnewline
0.99 & 18164.3826075062 & 310.441354864667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=47347&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]-3485.21954442343[/C][C]1371.49171598565[/C][/ROW]
[ROW][C]0.02[/C][C]-2927.21277172721[/C][C]1221.80543046011[/C][/ROW]
[ROW][C]0.03[/C][C]-2302.80702445408[/C][C]1245.69847421367[/C][/ROW]
[ROW][C]0.04[/C][C]-1670.20647216124[/C][C]1423.7059458641[/C][/ROW]
[ROW][C]0.05[/C][C]-1037.17453076282[/C][C]1644.05237749834[/C][/ROW]
[ROW][C]0.06[/C][C]-398.488184778689[/C][C]1828.43038895629[/C][/ROW]
[ROW][C]0.07[/C][C]244.390268322857[/C][C]1947.17168563160[/C][/ROW]
[ROW][C]0.08[/C][C]881.411663922053[/C][C]1997.79364221407[/C][/ROW]
[ROW][C]0.09[/C][C]1498.69666721703[/C][C]1987.18340269255[/C][/ROW]
[ROW][C]0.1[/C][C]2082.86713006288[/C][C]1923.12099569924[/C][/ROW]
[ROW][C]0.11[/C][C]2623.21815674378[/C][C]1813.27823103326[/C][/ROW]
[ROW][C]0.12[/C][C]3112.39917492086[/C][C]1667.12743132668[/C][/ROW]
[ROW][C]0.13[/C][C]3546.48092057943[/C][C]1497.00932811755[/C][/ROW]
[ROW][C]0.14[/C][C]3924.80364484911[/C][C]1317.20385386182[/C][/ROW]
[ROW][C]0.15[/C][C]4249.6394133436[/C][C]1141.73822139112[/C][/ROW]
[ROW][C]0.16[/C][C]4525.61993034268[/C][C]982.116920476027[/C][/ROW]
[ROW][C]0.17[/C][C]4758.96080748693[/C][C]845.80926246947[/C][/ROW]
[ROW][C]0.18[/C][C]4956.60672487552[/C][C]735.836365981014[/C][/ROW]
[ROW][C]0.19[/C][C]5125.45343150264[/C][C]651.238839198401[/C][/ROW]
[ROW][C]0.2[/C][C]5271.76734812357[/C][C]588.371659683852[/C][/ROW]
[ROW][C]0.21[/C][C]5400.85378879167[/C][C]542.438099459218[/C][/ROW]
[ROW][C]0.22[/C][C]5516.95656878964[/C][C]508.883957036208[/C][/ROW]
[ROW][C]0.23[/C][C]5623.3275105865[/C][C]484.132145268391[/C][/ROW]
[ROW][C]0.24[/C][C]5722.38987103672[/C][C]465.779187981576[/C][/ROW]
[ROW][C]0.25[/C][C]5815.92890526705[/C][C]452.297088482552[/C][/ROW]
[ROW][C]0.26[/C][C]5905.26460191668[/C][C]442.693157138745[/C][/ROW]
[ROW][C]0.27[/C][C]5991.38552416656[/C][C]436.205057822798[/C][/ROW]
[ROW][C]0.28[/C][C]6075.04157086193[/C][C]432.124484228292[/C][/ROW]
[ROW][C]0.29[/C][C]6156.80436012914[/C][C]429.786934632162[/C][/ROW]
[ROW][C]0.3[/C][C]6237.10722332638[/C][C]428.601603721772[/C][/ROW]
[ROW][C]0.31[/C][C]6316.2748349796[/C][C]428.126627232274[/C][/ROW]
[ROW][C]0.32[/C][C]6394.54821578469[/C][C]428.093448247143[/C][/ROW]
[ROW][C]0.33[/C][C]6472.10668357674[/C][C]428.372084010026[/C][/ROW]
[ROW][C]0.34[/C][C]6549.08574415402[/C][C]428.953398017992[/C][/ROW]
[ROW][C]0.35[/C][C]6625.58929657122[/C][C]429.828346739295[/C][/ROW]
[ROW][C]0.36[/C][C]6701.69545229795[/C][C]430.951009986658[/C][/ROW]
[ROW][C]0.37[/C][C]6777.456900845[/C][C]432.186727364417[/C][/ROW]
[ROW][C]0.38[/C][C]6852.89824110624[/C][C]433.310791955179[/C][/ROW]
[ROW][C]0.39[/C][C]6928.01343661689[/C][C]434.080365110841[/C][/ROW]
[ROW][C]0.4[/C][C]7002.76631950682[/C][C]434.207461320138[/C][/ROW]
[ROW][C]0.41[/C][C]7077.09599631271[/C][C]433.500627921387[/C][/ROW]
[ROW][C]0.42[/C][C]7150.92747830073[/C][C]431.873833123186[/C][/ROW]
[ROW][C]0.43[/C][C]7224.18633877949[/C][C]429.379221879389[/C][/ROW]
[ROW][C]0.44[/C][C]7296.81510203605[/C][C]426.211736767662[/C][/ROW]
[ROW][C]0.45[/C][C]7368.7886431548[/C][C]422.697643540149[/C][/ROW]
[ROW][C]0.46[/C][C]7440.12616813154[/C][C]419.222508408162[/C][/ROW]
[ROW][C]0.47[/C][C]7510.89819934833[/C][C]416.180593132162[/C][/ROW]
[ROW][C]0.48[/C][C]7581.22813001729[/C][C]413.953376336508[/C][/ROW]
[ROW][C]0.49[/C][C]7651.28900384128[/C][C]412.829598082456[/C][/ROW]
[ROW][C]0.5[/C][C]7721.29693724092[/C][C]413.0521164666[/C][/ROW]
[ROW][C]0.51[/C][C]7791.50286002559[/C][C]414.756609279367[/C][/ROW]
[ROW][C]0.52[/C][C]7862.1839883472[/C][C]418.007315734516[/C][/ROW]
[ROW][C]0.53[/C][C]7933.63579439817[/C][C]422.879582672516[/C][/ROW]
[ROW][C]0.54[/C][C]8006.16444441511[/C][C]429.40077580874[/C][/ROW]
[ROW][C]0.55[/C][C]8080.07902484337[/C][C]437.573595505028[/C][/ROW]
[ROW][C]0.56[/C][C]8155.68260944082[/C][C]447.376562092808[/C][/ROW]
[ROW][C]0.57[/C][C]8233.26146579598[/C][C]458.703400567062[/C][/ROW]
[ROW][C]0.58[/C][C]8313.07242591762[/C][C]471.338029210586[/C][/ROW]
[ROW][C]0.59[/C][C]8395.32945884295[/C][C]484.972812116816[/C][/ROW]
[ROW][C]0.6[/C][C]8480.19147813024[/C][C]499.134839253549[/C][/ROW]
[ROW][C]0.61[/C][C]8567.75406549158[/C][C]513.298920158917[/C][/ROW]
[ROW][C]0.62[/C][C]8658.0478487429[/C][C]526.936369813005[/C][/ROW]
[ROW][C]0.63[/C][C]8751.04566425276[/C][C]539.595061073958[/C][/ROW]
[ROW][C]0.64[/C][C]8846.67949547148[/C][C]550.964383305532[/C][/ROW]
[ROW][C]0.65[/C][C]8944.8668144252[/C][C]560.958582076477[/C][/ROW]
[ROW][C]0.66[/C][C]9045.54472808888[/C][C]569.757996331137[/C][/ROW]
[ROW][C]0.67[/C][C]9148.70952574644[/C][C]577.772670862978[/C][/ROW]
[ROW][C]0.68[/C][C]9254.45890080733[/C][C]585.659000069094[/C][/ROW]
[ROW][C]0.69[/C][C]9363.03408469383[/C][C]594.260333837623[/C][/ROW]
[ROW][C]0.7[/C][C]9474.85901066377[/C][C]604.571427242958[/C][/ROW]
[ROW][C]0.71[/C][C]9590.57309411706[/C][C]617.722291025906[/C][/ROW]
[ROW][C]0.72[/C][C]9711.05327133536[/C][C]634.934750130777[/C][/ROW]
[ROW][C]0.73[/C][C]9837.42012496137[/C][C]657.480229327461[/C][/ROW]
[ROW][C]0.74[/C][C]9971.02333064443[/C][C]686.484859583161[/C][/ROW]
[ROW][C]0.75[/C][C]10113.4045711830[/C][C]722.765965354975[/C][/ROW]
[ROW][C]0.76[/C][C]10266.2422620300[/C][C]766.591182786837[/C][/ROW]
[ROW][C]0.77[/C][C]10431.2913026962[/C][C]817.540379611355[/C][/ROW]
[ROW][C]0.78[/C][C]10610.3399127147[/C][C]874.512143879417[/C][/ROW]
[ROW][C]0.79[/C][C]10805.2096420699[/C][C]936.131040098241[/C][/ROW]
[ROW][C]0.8[/C][C]11017.8181434409[/C][C]1001.29500324338[/C][/ROW]
[ROW][C]0.81[/C][C]11250.3030507091[/C][C]1069.80378638220[/C][/ROW]
[ROW][C]0.82[/C][C]11505.1699326672[/C][C]1142.87703404510[/C][/ROW]
[ROW][C]0.83[/C][C]11785.3861457935[/C][C]1223.00425165973[/C][/ROW]
[ROW][C]0.84[/C][C]12094.3123200091[/C][C]1312.96590539346[/C][/ROW]
[ROW][C]0.85[/C][C]12435.3659433578[/C][C]1413.92110117953[/C][/ROW]
[ROW][C]0.86[/C][C]12811.3650303016[/C][C]1523.09399649129[/C][/ROW]
[ROW][C]0.87[/C][C]13223.6058544506[/C][C]1632.21728145585[/C][/ROW]
[ROW][C]0.88[/C][C]13670.8616075814[/C][C]1727.60250381325[/C][/ROW]
[ROW][C]0.89[/C][C]14148.5946145291[/C][C]1792.44425888063[/C][/ROW]
[ROW][C]0.9[/C][C]14648.6877780623[/C][C]1810.77956307521[/C][/ROW]
[ROW][C]0.91[/C][C]15159.8794254438[/C][C]1771.99098022661[/C][/ROW]
[ROW][C]0.92[/C][C]15668.8517431457[/C][C]1673.98933633024[/C][/ROW]
[ROW][C]0.93[/C][C]16161.6777245894[/C][C]1523.62290959147[/C][/ROW]
[ROW][C]0.94[/C][C]16625.2125200254[/C][C]1333.79806189774[/C][/ROW]
[ROW][C]0.95[/C][C]17048.0865530673[/C][C]1118.97800347148[/C][/ROW]
[ROW][C]0.96[/C][C]17421.0965848904[/C][C]892.150252567762[/C][/ROW]
[ROW][C]0.97[/C][C]17736.7513944701[/C][C]666.221369248368[/C][/ROW]
[ROW][C]0.98[/C][C]17987.6391542415[/C][C]460.781656842277[/C][/ROW]
[ROW][C]0.99[/C][C]18164.3826075062[/C][C]310.441354864667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=47347&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=47347&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
0.01-3485.219544423431371.49171598565
0.02-2927.212771727211221.80543046011
0.03-2302.807024454081245.69847421367
0.04-1670.206472161241423.7059458641
0.05-1037.174530762821644.05237749834
0.06-398.4881847786891828.43038895629
0.07244.3902683228571947.17168563160
0.08881.4116639220531997.79364221407
0.091498.696667217031987.18340269255
0.12082.867130062881923.12099569924
0.112623.218156743781813.27823103326
0.123112.399174920861667.12743132668
0.133546.480920579431497.00932811755
0.143924.803644849111317.20385386182
0.154249.63941334361141.73822139112
0.164525.61993034268982.116920476027
0.174758.96080748693845.80926246947
0.184956.60672487552735.836365981014
0.195125.45343150264651.238839198401
0.25271.76734812357588.371659683852
0.215400.85378879167542.438099459218
0.225516.95656878964508.883957036208
0.235623.3275105865484.132145268391
0.245722.38987103672465.779187981576
0.255815.92890526705452.297088482552
0.265905.26460191668442.693157138745
0.275991.38552416656436.205057822798
0.286075.04157086193432.124484228292
0.296156.80436012914429.786934632162
0.36237.10722332638428.601603721772
0.316316.2748349796428.126627232274
0.326394.54821578469428.093448247143
0.336472.10668357674428.372084010026
0.346549.08574415402428.953398017992
0.356625.58929657122429.828346739295
0.366701.69545229795430.951009986658
0.376777.456900845432.186727364417
0.386852.89824110624433.310791955179
0.396928.01343661689434.080365110841
0.47002.76631950682434.207461320138
0.417077.09599631271433.500627921387
0.427150.92747830073431.873833123186
0.437224.18633877949429.379221879389
0.447296.81510203605426.211736767662
0.457368.7886431548422.697643540149
0.467440.12616813154419.222508408162
0.477510.89819934833416.180593132162
0.487581.22813001729413.953376336508
0.497651.28900384128412.829598082456
0.57721.29693724092413.0521164666
0.517791.50286002559414.756609279367
0.527862.1839883472418.007315734516
0.537933.63579439817422.879582672516
0.548006.16444441511429.40077580874
0.558080.07902484337437.573595505028
0.568155.68260944082447.376562092808
0.578233.26146579598458.703400567062
0.588313.07242591762471.338029210586
0.598395.32945884295484.972812116816
0.68480.19147813024499.134839253549
0.618567.75406549158513.298920158917
0.628658.0478487429526.936369813005
0.638751.04566425276539.595061073958
0.648846.67949547148550.964383305532
0.658944.8668144252560.958582076477
0.669045.54472808888569.757996331137
0.679148.70952574644577.772670862978
0.689254.45890080733585.659000069094
0.699363.03408469383594.260333837623
0.79474.85901066377604.571427242958
0.719590.57309411706617.722291025906
0.729711.05327133536634.934750130777
0.739837.42012496137657.480229327461
0.749971.02333064443686.484859583161
0.7510113.4045711830722.765965354975
0.7610266.2422620300766.591182786837
0.7710431.2913026962817.540379611355
0.7810610.3399127147874.512143879417
0.7910805.2096420699936.131040098241
0.811017.81814344091001.29500324338
0.8111250.30305070911069.80378638220
0.8211505.16993266721142.87703404510
0.8311785.38614579351223.00425165973
0.8412094.31232000911312.96590539346
0.8512435.36594335781413.92110117953
0.8612811.36503030161523.09399649129
0.8713223.60585445061632.21728145585
0.8813670.86160758141727.60250381325
0.8914148.59461452911792.44425888063
0.914648.68777806231810.77956307521
0.9115159.87942544381771.99098022661
0.9215668.85174314571673.98933633024
0.9316161.67772458941523.62290959147
0.9416625.21252002541333.79806189774
0.9517048.08655306731118.97800347148
0.9617421.0965848904892.150252567762
0.9717736.7513944701666.221369248368
0.9817987.6391542415460.781656842277
0.9918164.3826075062310.441354864667


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')