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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 computationTue, 20 Oct 2009 11:39:07 -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/20/t1256060429hqzqx3pwivyxcx2.htm/, Retrieved Fri, 03 May 2024 03:42:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=48877, Retrieved Fri, 03 May 2024 03:42:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
F RMPD    [Univariate Data Series] [] [2009-10-14 08:30:28] [74be16979710d4c4e7c6647856088456]
-   PD      [Univariate Data Series] [WS3V2] [2009-10-20 17:25:41] [90e6802d28d0afa9b030a19cd25ed2b0]
- RMP           [Harrell-Davis Quantiles] [WS3V3] [2009-10-20 17:39:07] [40cfc51151e9382b81a5fb0c269b074d] [Current]
Feedback Forum

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516141
528222
532638
536322
536535
523597
536214
586570
596594
580523

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=48877&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=48877&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=48877&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'RServer@AstonUniversity' @ vre.aston.ac.uk






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01471875.1705476738601.31940161413
0.02475942.4581310629314.627636643
0.03480592.8609741489574.58926897382
0.04485107.0619352959208.5444495559
0.05489148.4401909658540.27227259164
0.06492647.8010191477901.55097596474
0.07495662.8455501327406.28918482944
0.08498285.8956455047015.96913700592
0.09500600.6559888286670.35975229902
0.1502670.5774791786343.93336644032
0.11504542.0908823056045.59705418673
0.12506251.4987695575796.88488314003
0.13507830.144482465616.16542758516
0.14509306.656459515511.8397103429
0.15510707.080208175481.46349423587
0.16512054.1083910315514.18242636079
0.17513366.2659132425594.10357119508
0.18514657.4347444125703.85828904235
0.19515936.7888567445826.31110564436
0.2517209.0827193545943.19525561936
0.21518475.2245238656038.62834967103
0.22519733.0869740346099.66196575941
0.23520978.5152535126119.15433367183
0.24522206.4719665296096.27197536711
0.25523412.2258067866037.62030641366
0.26524592.4659810815956.56574623858
0.27525746.2236224325869.15755191036
0.28526875.5073966295799.32483057598
0.29527985.6040886225767.4644767933
0.3529085.0411351335793.7997345857
0.31530185.2434383895897.13467595317
0.32531299.9348990786089.49831782131
0.33532444.3378530246378.48909320292
0.34533634.2188976196764.9585571357
0.35534884.8268843347241.96857102826
0.36536209.7746231367795.88807492376
0.37537619.9309329718405.55946612768
0.38539122.4091042629042.78735847175
0.39540719.7529514279676.55571215077
0.4542409.42347991510271.7051563212
0.41544183.6719210310796.2374909661
0.42546029.84795310811219.5751528240
0.43547931.1405087411519.8155553826
0.44549867.69218803411681.4774985849
0.45551817.97819125311700.5450610504
0.46553760.30677614611581.0641178181
0.47555674.28665311211337.1557628109
0.48557542.11844916510988.3152388437
0.49559349.59841012610562.1751025707
0.5561086.76532073710085.6346990985
0.51562748.1672915739588.6901512064
0.52564332.7656051929098.47041276703
0.53565843.5229327388637.8751125469
0.54567286.7411164328227.46247985963
0.55568671.2207834497879.35151599318
0.56570007.3148378517602.22615953981
0.57571305.9444288167395.6583770572
0.58572577.6424027257256.51190835724
0.59573831.6866414297171.70894516384
0.6575075.3830362567126.33308196618
0.61576313.5525670517101.85439856127
0.62577548.2661237497079.60706498696
0.63578778.8524553147041.40608414352
0.64580002.1792799976971.09496858374
0.65581213.1781480626859.50785027354
0.66582405.5554402956701.62711046474
0.67583572.611365846496.60325967982
0.68584708.0817894386251.21327372485
0.69585806.9273582835974.91090313542
0.7586866.019652045680.50519828015
0.71587884.708815315383.83501161749
0.72588865.2905768965101.01322278995
0.73589813.4092770564848.53993071941
0.74590738.4250046784645.4563676769
0.75591653.730470774511.04274738538
0.76592576.9310117164466.17041991129
0.77593529.7178593614533.80578010201
0.78594537.203468714733.29532108325
0.79595626.4887515685072.51735189718
0.8596824.3297987755544.17173129638
0.81598153.9756898716117.77641096564
0.82599631.5280200836743.38496598513
0.83601262.4509636557353.7250059738
0.84603039.0353389557875.3805458997
0.85604939.6011499158239.21645349151
0.86606929.9791109018392.30456815709
0.87608967.3940404768308.64222920581
0.88611006.3896483827995.21699895235
0.89613005.974212497488.47644836296
0.9614936.7270086656852.86138866396
0.91616786.1120951376168.79532931764
0.92618559.7335590145524.96668112195
0.93620276.1435788144994.24130995825
0.94621953.9399067364595.17428658858
0.95623593.0712660654251.95217570072
0.96625157.0920397513809.66405159036
0.97626566.8581773493123.17209789509
0.98627714.7530258442182.66787469975
0.99628500.8524156281211.35461605461

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 471875.170547673 & 8601.31940161413 \tabularnewline
0.02 & 475942.458131062 & 9314.627636643 \tabularnewline
0.03 & 480592.860974148 & 9574.58926897382 \tabularnewline
0.04 & 485107.061935295 & 9208.5444495559 \tabularnewline
0.05 & 489148.440190965 & 8540.27227259164 \tabularnewline
0.06 & 492647.801019147 & 7901.55097596474 \tabularnewline
0.07 & 495662.845550132 & 7406.28918482944 \tabularnewline
0.08 & 498285.895645504 & 7015.96913700592 \tabularnewline
0.09 & 500600.655988828 & 6670.35975229902 \tabularnewline
0.1 & 502670.577479178 & 6343.93336644032 \tabularnewline
0.11 & 504542.090882305 & 6045.59705418673 \tabularnewline
0.12 & 506251.498769557 & 5796.88488314003 \tabularnewline
0.13 & 507830.14448246 & 5616.16542758516 \tabularnewline
0.14 & 509306.65645951 & 5511.8397103429 \tabularnewline
0.15 & 510707.08020817 & 5481.46349423587 \tabularnewline
0.16 & 512054.108391031 & 5514.18242636079 \tabularnewline
0.17 & 513366.265913242 & 5594.10357119508 \tabularnewline
0.18 & 514657.434744412 & 5703.85828904235 \tabularnewline
0.19 & 515936.788856744 & 5826.31110564436 \tabularnewline
0.2 & 517209.082719354 & 5943.19525561936 \tabularnewline
0.21 & 518475.224523865 & 6038.62834967103 \tabularnewline
0.22 & 519733.086974034 & 6099.66196575941 \tabularnewline
0.23 & 520978.515253512 & 6119.15433367183 \tabularnewline
0.24 & 522206.471966529 & 6096.27197536711 \tabularnewline
0.25 & 523412.225806786 & 6037.62030641366 \tabularnewline
0.26 & 524592.465981081 & 5956.56574623858 \tabularnewline
0.27 & 525746.223622432 & 5869.15755191036 \tabularnewline
0.28 & 526875.507396629 & 5799.32483057598 \tabularnewline
0.29 & 527985.604088622 & 5767.4644767933 \tabularnewline
0.3 & 529085.041135133 & 5793.7997345857 \tabularnewline
0.31 & 530185.243438389 & 5897.13467595317 \tabularnewline
0.32 & 531299.934899078 & 6089.49831782131 \tabularnewline
0.33 & 532444.337853024 & 6378.48909320292 \tabularnewline
0.34 & 533634.218897619 & 6764.9585571357 \tabularnewline
0.35 & 534884.826884334 & 7241.96857102826 \tabularnewline
0.36 & 536209.774623136 & 7795.88807492376 \tabularnewline
0.37 & 537619.930932971 & 8405.55946612768 \tabularnewline
0.38 & 539122.409104262 & 9042.78735847175 \tabularnewline
0.39 & 540719.752951427 & 9676.55571215077 \tabularnewline
0.4 & 542409.423479915 & 10271.7051563212 \tabularnewline
0.41 & 544183.67192103 & 10796.2374909661 \tabularnewline
0.42 & 546029.847953108 & 11219.5751528240 \tabularnewline
0.43 & 547931.14050874 & 11519.8155553826 \tabularnewline
0.44 & 549867.692188034 & 11681.4774985849 \tabularnewline
0.45 & 551817.978191253 & 11700.5450610504 \tabularnewline
0.46 & 553760.306776146 & 11581.0641178181 \tabularnewline
0.47 & 555674.286653112 & 11337.1557628109 \tabularnewline
0.48 & 557542.118449165 & 10988.3152388437 \tabularnewline
0.49 & 559349.598410126 & 10562.1751025707 \tabularnewline
0.5 & 561086.765320737 & 10085.6346990985 \tabularnewline
0.51 & 562748.167291573 & 9588.6901512064 \tabularnewline
0.52 & 564332.765605192 & 9098.47041276703 \tabularnewline
0.53 & 565843.522932738 & 8637.8751125469 \tabularnewline
0.54 & 567286.741116432 & 8227.46247985963 \tabularnewline
0.55 & 568671.220783449 & 7879.35151599318 \tabularnewline
0.56 & 570007.314837851 & 7602.22615953981 \tabularnewline
0.57 & 571305.944428816 & 7395.6583770572 \tabularnewline
0.58 & 572577.642402725 & 7256.51190835724 \tabularnewline
0.59 & 573831.686641429 & 7171.70894516384 \tabularnewline
0.6 & 575075.383036256 & 7126.33308196618 \tabularnewline
0.61 & 576313.552567051 & 7101.85439856127 \tabularnewline
0.62 & 577548.266123749 & 7079.60706498696 \tabularnewline
0.63 & 578778.852455314 & 7041.40608414352 \tabularnewline
0.64 & 580002.179279997 & 6971.09496858374 \tabularnewline
0.65 & 581213.178148062 & 6859.50785027354 \tabularnewline
0.66 & 582405.555440295 & 6701.62711046474 \tabularnewline
0.67 & 583572.61136584 & 6496.60325967982 \tabularnewline
0.68 & 584708.081789438 & 6251.21327372485 \tabularnewline
0.69 & 585806.927358283 & 5974.91090313542 \tabularnewline
0.7 & 586866.01965204 & 5680.50519828015 \tabularnewline
0.71 & 587884.70881531 & 5383.83501161749 \tabularnewline
0.72 & 588865.290576896 & 5101.01322278995 \tabularnewline
0.73 & 589813.409277056 & 4848.53993071941 \tabularnewline
0.74 & 590738.425004678 & 4645.4563676769 \tabularnewline
0.75 & 591653.73047077 & 4511.04274738538 \tabularnewline
0.76 & 592576.931011716 & 4466.17041991129 \tabularnewline
0.77 & 593529.717859361 & 4533.80578010201 \tabularnewline
0.78 & 594537.20346871 & 4733.29532108325 \tabularnewline
0.79 & 595626.488751568 & 5072.51735189718 \tabularnewline
0.8 & 596824.329798775 & 5544.17173129638 \tabularnewline
0.81 & 598153.975689871 & 6117.77641096564 \tabularnewline
0.82 & 599631.528020083 & 6743.38496598513 \tabularnewline
0.83 & 601262.450963655 & 7353.7250059738 \tabularnewline
0.84 & 603039.035338955 & 7875.3805458997 \tabularnewline
0.85 & 604939.601149915 & 8239.21645349151 \tabularnewline
0.86 & 606929.979110901 & 8392.30456815709 \tabularnewline
0.87 & 608967.394040476 & 8308.64222920581 \tabularnewline
0.88 & 611006.389648382 & 7995.21699895235 \tabularnewline
0.89 & 613005.97421249 & 7488.47644836296 \tabularnewline
0.9 & 614936.727008665 & 6852.86138866396 \tabularnewline
0.91 & 616786.112095137 & 6168.79532931764 \tabularnewline
0.92 & 618559.733559014 & 5524.96668112195 \tabularnewline
0.93 & 620276.143578814 & 4994.24130995825 \tabularnewline
0.94 & 621953.939906736 & 4595.17428658858 \tabularnewline
0.95 & 623593.071266065 & 4251.95217570072 \tabularnewline
0.96 & 625157.092039751 & 3809.66405159036 \tabularnewline
0.97 & 626566.858177349 & 3123.17209789509 \tabularnewline
0.98 & 627714.753025844 & 2182.66787469975 \tabularnewline
0.99 & 628500.852415628 & 1211.35461605461 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=48877&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]471875.170547673[/C][C]8601.31940161413[/C][/ROW]
[ROW][C]0.02[/C][C]475942.458131062[/C][C]9314.627636643[/C][/ROW]
[ROW][C]0.03[/C][C]480592.860974148[/C][C]9574.58926897382[/C][/ROW]
[ROW][C]0.04[/C][C]485107.061935295[/C][C]9208.5444495559[/C][/ROW]
[ROW][C]0.05[/C][C]489148.440190965[/C][C]8540.27227259164[/C][/ROW]
[ROW][C]0.06[/C][C]492647.801019147[/C][C]7901.55097596474[/C][/ROW]
[ROW][C]0.07[/C][C]495662.845550132[/C][C]7406.28918482944[/C][/ROW]
[ROW][C]0.08[/C][C]498285.895645504[/C][C]7015.96913700592[/C][/ROW]
[ROW][C]0.09[/C][C]500600.655988828[/C][C]6670.35975229902[/C][/ROW]
[ROW][C]0.1[/C][C]502670.577479178[/C][C]6343.93336644032[/C][/ROW]
[ROW][C]0.11[/C][C]504542.090882305[/C][C]6045.59705418673[/C][/ROW]
[ROW][C]0.12[/C][C]506251.498769557[/C][C]5796.88488314003[/C][/ROW]
[ROW][C]0.13[/C][C]507830.14448246[/C][C]5616.16542758516[/C][/ROW]
[ROW][C]0.14[/C][C]509306.65645951[/C][C]5511.8397103429[/C][/ROW]
[ROW][C]0.15[/C][C]510707.08020817[/C][C]5481.46349423587[/C][/ROW]
[ROW][C]0.16[/C][C]512054.108391031[/C][C]5514.18242636079[/C][/ROW]
[ROW][C]0.17[/C][C]513366.265913242[/C][C]5594.10357119508[/C][/ROW]
[ROW][C]0.18[/C][C]514657.434744412[/C][C]5703.85828904235[/C][/ROW]
[ROW][C]0.19[/C][C]515936.788856744[/C][C]5826.31110564436[/C][/ROW]
[ROW][C]0.2[/C][C]517209.082719354[/C][C]5943.19525561936[/C][/ROW]
[ROW][C]0.21[/C][C]518475.224523865[/C][C]6038.62834967103[/C][/ROW]
[ROW][C]0.22[/C][C]519733.086974034[/C][C]6099.66196575941[/C][/ROW]
[ROW][C]0.23[/C][C]520978.515253512[/C][C]6119.15433367183[/C][/ROW]
[ROW][C]0.24[/C][C]522206.471966529[/C][C]6096.27197536711[/C][/ROW]
[ROW][C]0.25[/C][C]523412.225806786[/C][C]6037.62030641366[/C][/ROW]
[ROW][C]0.26[/C][C]524592.465981081[/C][C]5956.56574623858[/C][/ROW]
[ROW][C]0.27[/C][C]525746.223622432[/C][C]5869.15755191036[/C][/ROW]
[ROW][C]0.28[/C][C]526875.507396629[/C][C]5799.32483057598[/C][/ROW]
[ROW][C]0.29[/C][C]527985.604088622[/C][C]5767.4644767933[/C][/ROW]
[ROW][C]0.3[/C][C]529085.041135133[/C][C]5793.7997345857[/C][/ROW]
[ROW][C]0.31[/C][C]530185.243438389[/C][C]5897.13467595317[/C][/ROW]
[ROW][C]0.32[/C][C]531299.934899078[/C][C]6089.49831782131[/C][/ROW]
[ROW][C]0.33[/C][C]532444.337853024[/C][C]6378.48909320292[/C][/ROW]
[ROW][C]0.34[/C][C]533634.218897619[/C][C]6764.9585571357[/C][/ROW]
[ROW][C]0.35[/C][C]534884.826884334[/C][C]7241.96857102826[/C][/ROW]
[ROW][C]0.36[/C][C]536209.774623136[/C][C]7795.88807492376[/C][/ROW]
[ROW][C]0.37[/C][C]537619.930932971[/C][C]8405.55946612768[/C][/ROW]
[ROW][C]0.38[/C][C]539122.409104262[/C][C]9042.78735847175[/C][/ROW]
[ROW][C]0.39[/C][C]540719.752951427[/C][C]9676.55571215077[/C][/ROW]
[ROW][C]0.4[/C][C]542409.423479915[/C][C]10271.7051563212[/C][/ROW]
[ROW][C]0.41[/C][C]544183.67192103[/C][C]10796.2374909661[/C][/ROW]
[ROW][C]0.42[/C][C]546029.847953108[/C][C]11219.5751528240[/C][/ROW]
[ROW][C]0.43[/C][C]547931.14050874[/C][C]11519.8155553826[/C][/ROW]
[ROW][C]0.44[/C][C]549867.692188034[/C][C]11681.4774985849[/C][/ROW]
[ROW][C]0.45[/C][C]551817.978191253[/C][C]11700.5450610504[/C][/ROW]
[ROW][C]0.46[/C][C]553760.306776146[/C][C]11581.0641178181[/C][/ROW]
[ROW][C]0.47[/C][C]555674.286653112[/C][C]11337.1557628109[/C][/ROW]
[ROW][C]0.48[/C][C]557542.118449165[/C][C]10988.3152388437[/C][/ROW]
[ROW][C]0.49[/C][C]559349.598410126[/C][C]10562.1751025707[/C][/ROW]
[ROW][C]0.5[/C][C]561086.765320737[/C][C]10085.6346990985[/C][/ROW]
[ROW][C]0.51[/C][C]562748.167291573[/C][C]9588.6901512064[/C][/ROW]
[ROW][C]0.52[/C][C]564332.765605192[/C][C]9098.47041276703[/C][/ROW]
[ROW][C]0.53[/C][C]565843.522932738[/C][C]8637.8751125469[/C][/ROW]
[ROW][C]0.54[/C][C]567286.741116432[/C][C]8227.46247985963[/C][/ROW]
[ROW][C]0.55[/C][C]568671.220783449[/C][C]7879.35151599318[/C][/ROW]
[ROW][C]0.56[/C][C]570007.314837851[/C][C]7602.22615953981[/C][/ROW]
[ROW][C]0.57[/C][C]571305.944428816[/C][C]7395.6583770572[/C][/ROW]
[ROW][C]0.58[/C][C]572577.642402725[/C][C]7256.51190835724[/C][/ROW]
[ROW][C]0.59[/C][C]573831.686641429[/C][C]7171.70894516384[/C][/ROW]
[ROW][C]0.6[/C][C]575075.383036256[/C][C]7126.33308196618[/C][/ROW]
[ROW][C]0.61[/C][C]576313.552567051[/C][C]7101.85439856127[/C][/ROW]
[ROW][C]0.62[/C][C]577548.266123749[/C][C]7079.60706498696[/C][/ROW]
[ROW][C]0.63[/C][C]578778.852455314[/C][C]7041.40608414352[/C][/ROW]
[ROW][C]0.64[/C][C]580002.179279997[/C][C]6971.09496858374[/C][/ROW]
[ROW][C]0.65[/C][C]581213.178148062[/C][C]6859.50785027354[/C][/ROW]
[ROW][C]0.66[/C][C]582405.555440295[/C][C]6701.62711046474[/C][/ROW]
[ROW][C]0.67[/C][C]583572.61136584[/C][C]6496.60325967982[/C][/ROW]
[ROW][C]0.68[/C][C]584708.081789438[/C][C]6251.21327372485[/C][/ROW]
[ROW][C]0.69[/C][C]585806.927358283[/C][C]5974.91090313542[/C][/ROW]
[ROW][C]0.7[/C][C]586866.01965204[/C][C]5680.50519828015[/C][/ROW]
[ROW][C]0.71[/C][C]587884.70881531[/C][C]5383.83501161749[/C][/ROW]
[ROW][C]0.72[/C][C]588865.290576896[/C][C]5101.01322278995[/C][/ROW]
[ROW][C]0.73[/C][C]589813.409277056[/C][C]4848.53993071941[/C][/ROW]
[ROW][C]0.74[/C][C]590738.425004678[/C][C]4645.4563676769[/C][/ROW]
[ROW][C]0.75[/C][C]591653.73047077[/C][C]4511.04274738538[/C][/ROW]
[ROW][C]0.76[/C][C]592576.931011716[/C][C]4466.17041991129[/C][/ROW]
[ROW][C]0.77[/C][C]593529.717859361[/C][C]4533.80578010201[/C][/ROW]
[ROW][C]0.78[/C][C]594537.20346871[/C][C]4733.29532108325[/C][/ROW]
[ROW][C]0.79[/C][C]595626.488751568[/C][C]5072.51735189718[/C][/ROW]
[ROW][C]0.8[/C][C]596824.329798775[/C][C]5544.17173129638[/C][/ROW]
[ROW][C]0.81[/C][C]598153.975689871[/C][C]6117.77641096564[/C][/ROW]
[ROW][C]0.82[/C][C]599631.528020083[/C][C]6743.38496598513[/C][/ROW]
[ROW][C]0.83[/C][C]601262.450963655[/C][C]7353.7250059738[/C][/ROW]
[ROW][C]0.84[/C][C]603039.035338955[/C][C]7875.3805458997[/C][/ROW]
[ROW][C]0.85[/C][C]604939.601149915[/C][C]8239.21645349151[/C][/ROW]
[ROW][C]0.86[/C][C]606929.979110901[/C][C]8392.30456815709[/C][/ROW]
[ROW][C]0.87[/C][C]608967.394040476[/C][C]8308.64222920581[/C][/ROW]
[ROW][C]0.88[/C][C]611006.389648382[/C][C]7995.21699895235[/C][/ROW]
[ROW][C]0.89[/C][C]613005.97421249[/C][C]7488.47644836296[/C][/ROW]
[ROW][C]0.9[/C][C]614936.727008665[/C][C]6852.86138866396[/C][/ROW]
[ROW][C]0.91[/C][C]616786.112095137[/C][C]6168.79532931764[/C][/ROW]
[ROW][C]0.92[/C][C]618559.733559014[/C][C]5524.96668112195[/C][/ROW]
[ROW][C]0.93[/C][C]620276.143578814[/C][C]4994.24130995825[/C][/ROW]
[ROW][C]0.94[/C][C]621953.939906736[/C][C]4595.17428658858[/C][/ROW]
[ROW][C]0.95[/C][C]623593.071266065[/C][C]4251.95217570072[/C][/ROW]
[ROW][C]0.96[/C][C]625157.092039751[/C][C]3809.66405159036[/C][/ROW]
[ROW][C]0.97[/C][C]626566.858177349[/C][C]3123.17209789509[/C][/ROW]
[ROW][C]0.98[/C][C]627714.753025844[/C][C]2182.66787469975[/C][/ROW]
[ROW][C]0.99[/C][C]628500.852415628[/C][C]1211.35461605461[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=48877&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=48877&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
0.01471875.1705476738601.31940161413
0.02475942.4581310629314.627636643
0.03480592.8609741489574.58926897382
0.04485107.0619352959208.5444495559
0.05489148.4401909658540.27227259164
0.06492647.8010191477901.55097596474
0.07495662.8455501327406.28918482944
0.08498285.8956455047015.96913700592
0.09500600.6559888286670.35975229902
0.1502670.5774791786343.93336644032
0.11504542.0908823056045.59705418673
0.12506251.4987695575796.88488314003
0.13507830.144482465616.16542758516
0.14509306.656459515511.8397103429
0.15510707.080208175481.46349423587
0.16512054.1083910315514.18242636079
0.17513366.2659132425594.10357119508
0.18514657.4347444125703.85828904235
0.19515936.7888567445826.31110564436
0.2517209.0827193545943.19525561936
0.21518475.2245238656038.62834967103
0.22519733.0869740346099.66196575941
0.23520978.5152535126119.15433367183
0.24522206.4719665296096.27197536711
0.25523412.2258067866037.62030641366
0.26524592.4659810815956.56574623858
0.27525746.2236224325869.15755191036
0.28526875.5073966295799.32483057598
0.29527985.6040886225767.4644767933
0.3529085.0411351335793.7997345857
0.31530185.2434383895897.13467595317
0.32531299.9348990786089.49831782131
0.33532444.3378530246378.48909320292
0.34533634.2188976196764.9585571357
0.35534884.8268843347241.96857102826
0.36536209.7746231367795.88807492376
0.37537619.9309329718405.55946612768
0.38539122.4091042629042.78735847175
0.39540719.7529514279676.55571215077
0.4542409.42347991510271.7051563212
0.41544183.6719210310796.2374909661
0.42546029.84795310811219.5751528240
0.43547931.1405087411519.8155553826
0.44549867.69218803411681.4774985849
0.45551817.97819125311700.5450610504
0.46553760.30677614611581.0641178181
0.47555674.28665311211337.1557628109
0.48557542.11844916510988.3152388437
0.49559349.59841012610562.1751025707
0.5561086.76532073710085.6346990985
0.51562748.1672915739588.6901512064
0.52564332.7656051929098.47041276703
0.53565843.5229327388637.8751125469
0.54567286.7411164328227.46247985963
0.55568671.2207834497879.35151599318
0.56570007.3148378517602.22615953981
0.57571305.9444288167395.6583770572
0.58572577.6424027257256.51190835724
0.59573831.6866414297171.70894516384
0.6575075.3830362567126.33308196618
0.61576313.5525670517101.85439856127
0.62577548.2661237497079.60706498696
0.63578778.8524553147041.40608414352
0.64580002.1792799976971.09496858374
0.65581213.1781480626859.50785027354
0.66582405.5554402956701.62711046474
0.67583572.611365846496.60325967982
0.68584708.0817894386251.21327372485
0.69585806.9273582835974.91090313542
0.7586866.019652045680.50519828015
0.71587884.708815315383.83501161749
0.72588865.2905768965101.01322278995
0.73589813.4092770564848.53993071941
0.74590738.4250046784645.4563676769
0.75591653.730470774511.04274738538
0.76592576.9310117164466.17041991129
0.77593529.7178593614533.80578010201
0.78594537.203468714733.29532108325
0.79595626.4887515685072.51735189718
0.8596824.3297987755544.17173129638
0.81598153.9756898716117.77641096564
0.82599631.5280200836743.38496598513
0.83601262.4509636557353.7250059738
0.84603039.0353389557875.3805458997
0.85604939.6011499158239.21645349151
0.86606929.9791109018392.30456815709
0.87608967.3940404768308.64222920581
0.88611006.3896483827995.21699895235
0.89613005.974212497488.47644836296
0.9614936.7270086656852.86138866396
0.91616786.1120951376168.79532931764
0.92618559.7335590145524.96668112195
0.93620276.1435788144994.24130995825
0.94621953.9399067364595.17428658858
0.95623593.0712660654251.95217570072
0.96625157.0920397513809.66405159036
0.97626566.8581773493123.17209789509
0.98627714.7530258442182.66787469975
0.99628500.8524156281211.35461605461


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')