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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 computationMon, 26 May 2008 10:44:23 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/May/26/t1211820293hdsmy04x3sovjfw.htm/, Retrieved Mon, 13 May 2024 21:21:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13277, Retrieved Mon, 13 May 2024 21:21:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsPercentielen goudkoers KDG Stijn Cappaert
Estimated Impact194

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] [Percentielen goud...] [2008-05-26 16:44:23] [f38aed22bcf737d6f431a6f90e40d4b2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10236
10893
10756
10940
10997
10827
10166
10186
10457
10368
10244
10511
10812
10738
10171
9721
9897
9828
9924
10371
10846
10413
10709
10662
10570
10297
10635
10872
10296
10383
10431
10574
10653
10805
10872
10625
10407
10463
10556
10646
10702
11353
11346
11451
11964
12574
13031
13812
14544
14931
14886
16005
17064
15168
16050
15839
15137
14954
15648
15305
15579
16348
15928
16171
15937
15713
15594
15683
16438
17032
17696
17745
19394

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13277&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]6 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=13277&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13277&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 time6 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Harrell-Davis Quantiles
quantilesvaluestandard error
0.019756.4780813461897.8025861120295
0.029811.570980872997.548666876889
0.039872.29150824422110.451152492101
0.049932.90416156334126.767443430481
0.059991.72512071744135.498267282320
0.0610047.1169694633132.512014910209
0.0710097.1189933153120.421517687274
0.0810140.4625002319104.963731507888
0.0910177.122338025991.2839260442957
0.110208.087200235381.8972681234133
0.1110234.769584183076.6491199783664
0.1210258.488179169874.0717402363283
0.1310280.206979697972.6378035974386
0.1410300.507700602071.363644742514
0.1510319.690003234169.881400229764
0.1610337.902886622768.1900698919872
0.1710355.251665227166.597357451398
0.1810371.861552640165.4517537806665
0.1910387.900186587865.0957885676467
0.210403.570212073365.7202273040621
0.2110419.084825418467.3059309515806
0.2210434.637819742669.6616916140523
0.2310450.377015332272.4449648642759
0.2410466.386814518875.3053029635081
0.2510482.682468618077.8783125945255
0.2610499.215874425579.8848295862042
0.2710515.890624810381.1401720084011
0.2810532.582776409181.586904263482
0.2910549.163373921481.2953198659375
0.310565.519072048280.415713641285
0.3110581.568032315779.1635159008233
0.3210597.269418754277.796550886472
0.3310612.626055334976.5772184348331
0.3410627.680957088075.7123000078303
0.3510642.509376737275.3268326063916
0.3610657.208644861075.5323249840515
0.3710671.888394692876.3427739332033
0.3810686.663755693777.7311646350633
0.3910701.653798061679.6713846049458
0.410716.986955582882.1950175091695
0.4110732.814404627485.442856907674
0.4210749.331504667589.7042057294557
0.4310766.806491513895.5003785057696
0.4410785.6147385624103.552876526254
0.4510806.2761292534114.864983536964
0.4610829.4924527496130.629087326754
0.4710856.1812441485152.189946704675
0.4810887.5021043393180.952628813534
0.4910924.8712000761218.296300914186
0.510969.9593301168265.505595023460
0.5111024.6686893696323.66285532582
0.5211091.0834338299393.481521136576
0.5311171.3896545068475.186772032766
0.5411267.7618314096568.34409943875
0.5511382.2156870203671.634188803318
0.5611516.4318470538782.700611567348
0.5711671.5607144729898.096626847485
0.5811848.02578245881013.33644124871
0.5912045.34895850881123.06767252241
0.612262.02559196491221.40225867065
0.6112495.47694845431302.44600439721
0.6212742.10246133441360.82001309424
0.6312997.44283580231392.40407566839
0.6413256.44904954941394.77137071867
0.6513513.8340721071367.65069126011
0.6613764.46745227671312.98417791575
0.6714003.76187356251234.84716831853
0.6814227.99866829571138.84667864636
0.6914434.54760291911031.62900906648
0.714621.9539723472919.955811263991
0.7114789.8896016948810.006667065743
0.7214938.9883974309706.749310450332
0.7315070.6058861394613.581202029485
0.7415186.5512826998532.1879147217
0.7515288.8382805816462.818487051759
0.7615379.4885021315404.659126725308
0.7715460.403790796356.364391917659
0.7815533.3060701230316.498446981416
0.7915599.7315086429283.833783575257
0.815661.0619071618257.446361325412
0.8115718.5798454882236.693661654219
0.8215773.5414927982221.164306216096
0.8315827.2670950867210.760358808291
0.8415881.2498372816205.782694740454
0.8515937.2772937198207.020570004375
0.8615997.5470979031215.717015835610
0.8716064.7432189526233.204619994209
0.8816142.0269821055260.405809585701
0.8916232.8959767781297.217178408789
0.916340.8841184371341.916983934485
0.9116469.1263450157390.76841706146
0.9216619.9105174016438.236846771156
0.9316794.5696931312478.01173533992
0.9416994.6312979483504.703317700836
0.9517226.0344576582517.253678773082
0.9617507.7317879609530.935768676873
0.9717878.4303992263608.72494238326
0.9818375.6896515355855.375600213222
0.9918953.86778541951266.66235726978

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 9756.47808134618 & 97.8025861120295 \tabularnewline
0.02 & 9811.5709808729 & 97.548666876889 \tabularnewline
0.03 & 9872.29150824422 & 110.451152492101 \tabularnewline
0.04 & 9932.90416156334 & 126.767443430481 \tabularnewline
0.05 & 9991.72512071744 & 135.498267282320 \tabularnewline
0.06 & 10047.1169694633 & 132.512014910209 \tabularnewline
0.07 & 10097.1189933153 & 120.421517687274 \tabularnewline
0.08 & 10140.4625002319 & 104.963731507888 \tabularnewline
0.09 & 10177.1223380259 & 91.2839260442957 \tabularnewline
0.1 & 10208.0872002353 & 81.8972681234133 \tabularnewline
0.11 & 10234.7695841830 & 76.6491199783664 \tabularnewline
0.12 & 10258.4881791698 & 74.0717402363283 \tabularnewline
0.13 & 10280.2069796979 & 72.6378035974386 \tabularnewline
0.14 & 10300.5077006020 & 71.363644742514 \tabularnewline
0.15 & 10319.6900032341 & 69.881400229764 \tabularnewline
0.16 & 10337.9028866227 & 68.1900698919872 \tabularnewline
0.17 & 10355.2516652271 & 66.597357451398 \tabularnewline
0.18 & 10371.8615526401 & 65.4517537806665 \tabularnewline
0.19 & 10387.9001865878 & 65.0957885676467 \tabularnewline
0.2 & 10403.5702120733 & 65.7202273040621 \tabularnewline
0.21 & 10419.0848254184 & 67.3059309515806 \tabularnewline
0.22 & 10434.6378197426 & 69.6616916140523 \tabularnewline
0.23 & 10450.3770153322 & 72.4449648642759 \tabularnewline
0.24 & 10466.3868145188 & 75.3053029635081 \tabularnewline
0.25 & 10482.6824686180 & 77.8783125945255 \tabularnewline
0.26 & 10499.2158744255 & 79.8848295862042 \tabularnewline
0.27 & 10515.8906248103 & 81.1401720084011 \tabularnewline
0.28 & 10532.5827764091 & 81.586904263482 \tabularnewline
0.29 & 10549.1633739214 & 81.2953198659375 \tabularnewline
0.3 & 10565.5190720482 & 80.415713641285 \tabularnewline
0.31 & 10581.5680323157 & 79.1635159008233 \tabularnewline
0.32 & 10597.2694187542 & 77.796550886472 \tabularnewline
0.33 & 10612.6260553349 & 76.5772184348331 \tabularnewline
0.34 & 10627.6809570880 & 75.7123000078303 \tabularnewline
0.35 & 10642.5093767372 & 75.3268326063916 \tabularnewline
0.36 & 10657.2086448610 & 75.5323249840515 \tabularnewline
0.37 & 10671.8883946928 & 76.3427739332033 \tabularnewline
0.38 & 10686.6637556937 & 77.7311646350633 \tabularnewline
0.39 & 10701.6537980616 & 79.6713846049458 \tabularnewline
0.4 & 10716.9869555828 & 82.1950175091695 \tabularnewline
0.41 & 10732.8144046274 & 85.442856907674 \tabularnewline
0.42 & 10749.3315046675 & 89.7042057294557 \tabularnewline
0.43 & 10766.8064915138 & 95.5003785057696 \tabularnewline
0.44 & 10785.6147385624 & 103.552876526254 \tabularnewline
0.45 & 10806.2761292534 & 114.864983536964 \tabularnewline
0.46 & 10829.4924527496 & 130.629087326754 \tabularnewline
0.47 & 10856.1812441485 & 152.189946704675 \tabularnewline
0.48 & 10887.5021043393 & 180.952628813534 \tabularnewline
0.49 & 10924.8712000761 & 218.296300914186 \tabularnewline
0.5 & 10969.9593301168 & 265.505595023460 \tabularnewline
0.51 & 11024.6686893696 & 323.66285532582 \tabularnewline
0.52 & 11091.0834338299 & 393.481521136576 \tabularnewline
0.53 & 11171.3896545068 & 475.186772032766 \tabularnewline
0.54 & 11267.7618314096 & 568.34409943875 \tabularnewline
0.55 & 11382.2156870203 & 671.634188803318 \tabularnewline
0.56 & 11516.4318470538 & 782.700611567348 \tabularnewline
0.57 & 11671.5607144729 & 898.096626847485 \tabularnewline
0.58 & 11848.0257824588 & 1013.33644124871 \tabularnewline
0.59 & 12045.3489585088 & 1123.06767252241 \tabularnewline
0.6 & 12262.0255919649 & 1221.40225867065 \tabularnewline
0.61 & 12495.4769484543 & 1302.44600439721 \tabularnewline
0.62 & 12742.1024613344 & 1360.82001309424 \tabularnewline
0.63 & 12997.4428358023 & 1392.40407566839 \tabularnewline
0.64 & 13256.4490495494 & 1394.77137071867 \tabularnewline
0.65 & 13513.834072107 & 1367.65069126011 \tabularnewline
0.66 & 13764.4674522767 & 1312.98417791575 \tabularnewline
0.67 & 14003.7618735625 & 1234.84716831853 \tabularnewline
0.68 & 14227.9986682957 & 1138.84667864636 \tabularnewline
0.69 & 14434.5476029191 & 1031.62900906648 \tabularnewline
0.7 & 14621.9539723472 & 919.955811263991 \tabularnewline
0.71 & 14789.8896016948 & 810.006667065743 \tabularnewline
0.72 & 14938.9883974309 & 706.749310450332 \tabularnewline
0.73 & 15070.6058861394 & 613.581202029485 \tabularnewline
0.74 & 15186.5512826998 & 532.1879147217 \tabularnewline
0.75 & 15288.8382805816 & 462.818487051759 \tabularnewline
0.76 & 15379.4885021315 & 404.659126725308 \tabularnewline
0.77 & 15460.403790796 & 356.364391917659 \tabularnewline
0.78 & 15533.3060701230 & 316.498446981416 \tabularnewline
0.79 & 15599.7315086429 & 283.833783575257 \tabularnewline
0.8 & 15661.0619071618 & 257.446361325412 \tabularnewline
0.81 & 15718.5798454882 & 236.693661654219 \tabularnewline
0.82 & 15773.5414927982 & 221.164306216096 \tabularnewline
0.83 & 15827.2670950867 & 210.760358808291 \tabularnewline
0.84 & 15881.2498372816 & 205.782694740454 \tabularnewline
0.85 & 15937.2772937198 & 207.020570004375 \tabularnewline
0.86 & 15997.5470979031 & 215.717015835610 \tabularnewline
0.87 & 16064.7432189526 & 233.204619994209 \tabularnewline
0.88 & 16142.0269821055 & 260.405809585701 \tabularnewline
0.89 & 16232.8959767781 & 297.217178408789 \tabularnewline
0.9 & 16340.8841184371 & 341.916983934485 \tabularnewline
0.91 & 16469.1263450157 & 390.76841706146 \tabularnewline
0.92 & 16619.9105174016 & 438.236846771156 \tabularnewline
0.93 & 16794.5696931312 & 478.01173533992 \tabularnewline
0.94 & 16994.6312979483 & 504.703317700836 \tabularnewline
0.95 & 17226.0344576582 & 517.253678773082 \tabularnewline
0.96 & 17507.7317879609 & 530.935768676873 \tabularnewline
0.97 & 17878.4303992263 & 608.72494238326 \tabularnewline
0.98 & 18375.6896515355 & 855.375600213222 \tabularnewline
0.99 & 18953.8677854195 & 1266.66235726978 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13277&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]9756.47808134618[/C][C]97.8025861120295[/C][/ROW]
[ROW][C]0.02[/C][C]9811.5709808729[/C][C]97.548666876889[/C][/ROW]
[ROW][C]0.03[/C][C]9872.29150824422[/C][C]110.451152492101[/C][/ROW]
[ROW][C]0.04[/C][C]9932.90416156334[/C][C]126.767443430481[/C][/ROW]
[ROW][C]0.05[/C][C]9991.72512071744[/C][C]135.498267282320[/C][/ROW]
[ROW][C]0.06[/C][C]10047.1169694633[/C][C]132.512014910209[/C][/ROW]
[ROW][C]0.07[/C][C]10097.1189933153[/C][C]120.421517687274[/C][/ROW]
[ROW][C]0.08[/C][C]10140.4625002319[/C][C]104.963731507888[/C][/ROW]
[ROW][C]0.09[/C][C]10177.1223380259[/C][C]91.2839260442957[/C][/ROW]
[ROW][C]0.1[/C][C]10208.0872002353[/C][C]81.8972681234133[/C][/ROW]
[ROW][C]0.11[/C][C]10234.7695841830[/C][C]76.6491199783664[/C][/ROW]
[ROW][C]0.12[/C][C]10258.4881791698[/C][C]74.0717402363283[/C][/ROW]
[ROW][C]0.13[/C][C]10280.2069796979[/C][C]72.6378035974386[/C][/ROW]
[ROW][C]0.14[/C][C]10300.5077006020[/C][C]71.363644742514[/C][/ROW]
[ROW][C]0.15[/C][C]10319.6900032341[/C][C]69.881400229764[/C][/ROW]
[ROW][C]0.16[/C][C]10337.9028866227[/C][C]68.1900698919872[/C][/ROW]
[ROW][C]0.17[/C][C]10355.2516652271[/C][C]66.597357451398[/C][/ROW]
[ROW][C]0.18[/C][C]10371.8615526401[/C][C]65.4517537806665[/C][/ROW]
[ROW][C]0.19[/C][C]10387.9001865878[/C][C]65.0957885676467[/C][/ROW]
[ROW][C]0.2[/C][C]10403.5702120733[/C][C]65.7202273040621[/C][/ROW]
[ROW][C]0.21[/C][C]10419.0848254184[/C][C]67.3059309515806[/C][/ROW]
[ROW][C]0.22[/C][C]10434.6378197426[/C][C]69.6616916140523[/C][/ROW]
[ROW][C]0.23[/C][C]10450.3770153322[/C][C]72.4449648642759[/C][/ROW]
[ROW][C]0.24[/C][C]10466.3868145188[/C][C]75.3053029635081[/C][/ROW]
[ROW][C]0.25[/C][C]10482.6824686180[/C][C]77.8783125945255[/C][/ROW]
[ROW][C]0.26[/C][C]10499.2158744255[/C][C]79.8848295862042[/C][/ROW]
[ROW][C]0.27[/C][C]10515.8906248103[/C][C]81.1401720084011[/C][/ROW]
[ROW][C]0.28[/C][C]10532.5827764091[/C][C]81.586904263482[/C][/ROW]
[ROW][C]0.29[/C][C]10549.1633739214[/C][C]81.2953198659375[/C][/ROW]
[ROW][C]0.3[/C][C]10565.5190720482[/C][C]80.415713641285[/C][/ROW]
[ROW][C]0.31[/C][C]10581.5680323157[/C][C]79.1635159008233[/C][/ROW]
[ROW][C]0.32[/C][C]10597.2694187542[/C][C]77.796550886472[/C][/ROW]
[ROW][C]0.33[/C][C]10612.6260553349[/C][C]76.5772184348331[/C][/ROW]
[ROW][C]0.34[/C][C]10627.6809570880[/C][C]75.7123000078303[/C][/ROW]
[ROW][C]0.35[/C][C]10642.5093767372[/C][C]75.3268326063916[/C][/ROW]
[ROW][C]0.36[/C][C]10657.2086448610[/C][C]75.5323249840515[/C][/ROW]
[ROW][C]0.37[/C][C]10671.8883946928[/C][C]76.3427739332033[/C][/ROW]
[ROW][C]0.38[/C][C]10686.6637556937[/C][C]77.7311646350633[/C][/ROW]
[ROW][C]0.39[/C][C]10701.6537980616[/C][C]79.6713846049458[/C][/ROW]
[ROW][C]0.4[/C][C]10716.9869555828[/C][C]82.1950175091695[/C][/ROW]
[ROW][C]0.41[/C][C]10732.8144046274[/C][C]85.442856907674[/C][/ROW]
[ROW][C]0.42[/C][C]10749.3315046675[/C][C]89.7042057294557[/C][/ROW]
[ROW][C]0.43[/C][C]10766.8064915138[/C][C]95.5003785057696[/C][/ROW]
[ROW][C]0.44[/C][C]10785.6147385624[/C][C]103.552876526254[/C][/ROW]
[ROW][C]0.45[/C][C]10806.2761292534[/C][C]114.864983536964[/C][/ROW]
[ROW][C]0.46[/C][C]10829.4924527496[/C][C]130.629087326754[/C][/ROW]
[ROW][C]0.47[/C][C]10856.1812441485[/C][C]152.189946704675[/C][/ROW]
[ROW][C]0.48[/C][C]10887.5021043393[/C][C]180.952628813534[/C][/ROW]
[ROW][C]0.49[/C][C]10924.8712000761[/C][C]218.296300914186[/C][/ROW]
[ROW][C]0.5[/C][C]10969.9593301168[/C][C]265.505595023460[/C][/ROW]
[ROW][C]0.51[/C][C]11024.6686893696[/C][C]323.66285532582[/C][/ROW]
[ROW][C]0.52[/C][C]11091.0834338299[/C][C]393.481521136576[/C][/ROW]
[ROW][C]0.53[/C][C]11171.3896545068[/C][C]475.186772032766[/C][/ROW]
[ROW][C]0.54[/C][C]11267.7618314096[/C][C]568.34409943875[/C][/ROW]
[ROW][C]0.55[/C][C]11382.2156870203[/C][C]671.634188803318[/C][/ROW]
[ROW][C]0.56[/C][C]11516.4318470538[/C][C]782.700611567348[/C][/ROW]
[ROW][C]0.57[/C][C]11671.5607144729[/C][C]898.096626847485[/C][/ROW]
[ROW][C]0.58[/C][C]11848.0257824588[/C][C]1013.33644124871[/C][/ROW]
[ROW][C]0.59[/C][C]12045.3489585088[/C][C]1123.06767252241[/C][/ROW]
[ROW][C]0.6[/C][C]12262.0255919649[/C][C]1221.40225867065[/C][/ROW]
[ROW][C]0.61[/C][C]12495.4769484543[/C][C]1302.44600439721[/C][/ROW]
[ROW][C]0.62[/C][C]12742.1024613344[/C][C]1360.82001309424[/C][/ROW]
[ROW][C]0.63[/C][C]12997.4428358023[/C][C]1392.40407566839[/C][/ROW]
[ROW][C]0.64[/C][C]13256.4490495494[/C][C]1394.77137071867[/C][/ROW]
[ROW][C]0.65[/C][C]13513.834072107[/C][C]1367.65069126011[/C][/ROW]
[ROW][C]0.66[/C][C]13764.4674522767[/C][C]1312.98417791575[/C][/ROW]
[ROW][C]0.67[/C][C]14003.7618735625[/C][C]1234.84716831853[/C][/ROW]
[ROW][C]0.68[/C][C]14227.9986682957[/C][C]1138.84667864636[/C][/ROW]
[ROW][C]0.69[/C][C]14434.5476029191[/C][C]1031.62900906648[/C][/ROW]
[ROW][C]0.7[/C][C]14621.9539723472[/C][C]919.955811263991[/C][/ROW]
[ROW][C]0.71[/C][C]14789.8896016948[/C][C]810.006667065743[/C][/ROW]
[ROW][C]0.72[/C][C]14938.9883974309[/C][C]706.749310450332[/C][/ROW]
[ROW][C]0.73[/C][C]15070.6058861394[/C][C]613.581202029485[/C][/ROW]
[ROW][C]0.74[/C][C]15186.5512826998[/C][C]532.1879147217[/C][/ROW]
[ROW][C]0.75[/C][C]15288.8382805816[/C][C]462.818487051759[/C][/ROW]
[ROW][C]0.76[/C][C]15379.4885021315[/C][C]404.659126725308[/C][/ROW]
[ROW][C]0.77[/C][C]15460.403790796[/C][C]356.364391917659[/C][/ROW]
[ROW][C]0.78[/C][C]15533.3060701230[/C][C]316.498446981416[/C][/ROW]
[ROW][C]0.79[/C][C]15599.7315086429[/C][C]283.833783575257[/C][/ROW]
[ROW][C]0.8[/C][C]15661.0619071618[/C][C]257.446361325412[/C][/ROW]
[ROW][C]0.81[/C][C]15718.5798454882[/C][C]236.693661654219[/C][/ROW]
[ROW][C]0.82[/C][C]15773.5414927982[/C][C]221.164306216096[/C][/ROW]
[ROW][C]0.83[/C][C]15827.2670950867[/C][C]210.760358808291[/C][/ROW]
[ROW][C]0.84[/C][C]15881.2498372816[/C][C]205.782694740454[/C][/ROW]
[ROW][C]0.85[/C][C]15937.2772937198[/C][C]207.020570004375[/C][/ROW]
[ROW][C]0.86[/C][C]15997.5470979031[/C][C]215.717015835610[/C][/ROW]
[ROW][C]0.87[/C][C]16064.7432189526[/C][C]233.204619994209[/C][/ROW]
[ROW][C]0.88[/C][C]16142.0269821055[/C][C]260.405809585701[/C][/ROW]
[ROW][C]0.89[/C][C]16232.8959767781[/C][C]297.217178408789[/C][/ROW]
[ROW][C]0.9[/C][C]16340.8841184371[/C][C]341.916983934485[/C][/ROW]
[ROW][C]0.91[/C][C]16469.1263450157[/C][C]390.76841706146[/C][/ROW]
[ROW][C]0.92[/C][C]16619.9105174016[/C][C]438.236846771156[/C][/ROW]
[ROW][C]0.93[/C][C]16794.5696931312[/C][C]478.01173533992[/C][/ROW]
[ROW][C]0.94[/C][C]16994.6312979483[/C][C]504.703317700836[/C][/ROW]
[ROW][C]0.95[/C][C]17226.0344576582[/C][C]517.253678773082[/C][/ROW]
[ROW][C]0.96[/C][C]17507.7317879609[/C][C]530.935768676873[/C][/ROW]
[ROW][C]0.97[/C][C]17878.4303992263[/C][C]608.72494238326[/C][/ROW]
[ROW][C]0.98[/C][C]18375.6896515355[/C][C]855.375600213222[/C][/ROW]
[ROW][C]0.99[/C][C]18953.8677854195[/C][C]1266.66235726978[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13277&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13277&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
0.019756.4780813461897.8025861120295
0.029811.570980872997.548666876889
0.039872.29150824422110.451152492101
0.049932.90416156334126.767443430481
0.059991.72512071744135.498267282320
0.0610047.1169694633132.512014910209
0.0710097.1189933153120.421517687274
0.0810140.4625002319104.963731507888
0.0910177.122338025991.2839260442957
0.110208.087200235381.8972681234133
0.1110234.769584183076.6491199783664
0.1210258.488179169874.0717402363283
0.1310280.206979697972.6378035974386
0.1410300.507700602071.363644742514
0.1510319.690003234169.881400229764
0.1610337.902886622768.1900698919872
0.1710355.251665227166.597357451398
0.1810371.861552640165.4517537806665
0.1910387.900186587865.0957885676467
0.210403.570212073365.7202273040621
0.2110419.084825418467.3059309515806
0.2210434.637819742669.6616916140523
0.2310450.377015332272.4449648642759
0.2410466.386814518875.3053029635081
0.2510482.682468618077.8783125945255
0.2610499.215874425579.8848295862042
0.2710515.890624810381.1401720084011
0.2810532.582776409181.586904263482
0.2910549.163373921481.2953198659375
0.310565.519072048280.415713641285
0.3110581.568032315779.1635159008233
0.3210597.269418754277.796550886472
0.3310612.626055334976.5772184348331
0.3410627.680957088075.7123000078303
0.3510642.509376737275.3268326063916
0.3610657.208644861075.5323249840515
0.3710671.888394692876.3427739332033
0.3810686.663755693777.7311646350633
0.3910701.653798061679.6713846049458
0.410716.986955582882.1950175091695
0.4110732.814404627485.442856907674
0.4210749.331504667589.7042057294557
0.4310766.806491513895.5003785057696
0.4410785.6147385624103.552876526254
0.4510806.2761292534114.864983536964
0.4610829.4924527496130.629087326754
0.4710856.1812441485152.189946704675
0.4810887.5021043393180.952628813534
0.4910924.8712000761218.296300914186
0.510969.9593301168265.505595023460
0.5111024.6686893696323.66285532582
0.5211091.0834338299393.481521136576
0.5311171.3896545068475.186772032766
0.5411267.7618314096568.34409943875
0.5511382.2156870203671.634188803318
0.5611516.4318470538782.700611567348
0.5711671.5607144729898.096626847485
0.5811848.02578245881013.33644124871
0.5912045.34895850881123.06767252241
0.612262.02559196491221.40225867065
0.6112495.47694845431302.44600439721
0.6212742.10246133441360.82001309424
0.6312997.44283580231392.40407566839
0.6413256.44904954941394.77137071867
0.6513513.8340721071367.65069126011
0.6613764.46745227671312.98417791575
0.6714003.76187356251234.84716831853
0.6814227.99866829571138.84667864636
0.6914434.54760291911031.62900906648
0.714621.9539723472919.955811263991
0.7114789.8896016948810.006667065743
0.7214938.9883974309706.749310450332
0.7315070.6058861394613.581202029485
0.7415186.5512826998532.1879147217
0.7515288.8382805816462.818487051759
0.7615379.4885021315404.659126725308
0.7715460.403790796356.364391917659
0.7815533.3060701230316.498446981416
0.7915599.7315086429283.833783575257
0.815661.0619071618257.446361325412
0.8115718.5798454882236.693661654219
0.8215773.5414927982221.164306216096
0.8315827.2670950867210.760358808291
0.8415881.2498372816205.782694740454
0.8515937.2772937198207.020570004375
0.8615997.5470979031215.717015835610
0.8716064.7432189526233.204619994209
0.8816142.0269821055260.405809585701
0.8916232.8959767781297.217178408789
0.916340.8841184371341.916983934485
0.9116469.1263450157390.76841706146
0.9216619.9105174016438.236846771156
0.9316794.5696931312478.01173533992
0.9416994.6312979483504.703317700836
0.9517226.0344576582517.253678773082
0.9617507.7317879609530.935768676873
0.9717878.4303992263608.72494238326
0.9818375.6896515355855.375600213222
0.9918953.86778541951266.66235726978


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')