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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 computationFri, 07 Aug 2015 14:03:56 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Aug/07/t1438952973owhizztd2x8xxaa.htm/, Retrieved Wed, 15 May 2024 23:08:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279893, Retrieved Wed, 15 May 2024 23:08:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsHarrel-Davis Percentielen Reeks A Sebastiaan Lunders Mercedes A-klasse omzet Ottevaere
Estimated Impact159

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Cijferreeks A 2de...] [2015-08-05 23:58:24] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP   [Kernel Density Estimation] [Dichtheidsgrafiek...] [2015-08-06 13:05:13] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP     [Notched Boxplots] [Notched Boxplots ...] [2015-08-06 15:26:45] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP       [Harrell-Davis Quantiles] [Decielen Reeks A ...] [2015-08-07 12:40:19] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- R P           [Harrell-Davis Quantiles] [Percentielen Reek...] [2015-08-07 13:03:56] [2cf7618d5ff65529ef2e27cea5366de0] [Current]
- RMP             [Central Tendency] [Central tendency ...] [2015-08-07 14:01:29] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP               [Mean Plot] [Mean plot Reeks A...] [2015-08-07 14:19:08] [039d3b62ab99f9eeb4c9cc4c099c66fc]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3221816.00
3209817.00
3197649.00
3172468.00
3421574.00
3408392.00
3221816.00
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1704872.00

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'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279893&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279893&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279893&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'George Udny Yule' @ yule.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.011131410.62811349191591.318860052
0.021295113.14863011126214.760646417
0.031404133.65595745109855.328250702
0.041486047.63184221128280.232414164
0.051562286.71407804140601.950858529
0.061633998.44047084132451.660886695
0.071696028.84071601112184.873635137
0.081746239.3928928392800.8798809595
0.091786706.0650661781716.1331103172
0.11821438.0951927580333.9948923573
0.111854327.6074086486988.0313667256
0.121888220.8183153298742.9553019287
0.131924683.19088772112176.302857399
0.141964058.24918124067.07869198
0.152005708.96230456132091.224353724
0.162048412.06956519135281.842800775
0.172090816.52517025134115.700867723
0.182131835.07417418130074.161078623
0.192170869.09040329125061.551779454
0.22207842.02639518120766.879526014
0.212243086.06870912118284.945061262
0.222277159.74311997117993.946494257
0.232310669.38957569119691.204270885
0.242344139.98982773122846.911288477
0.252377948.97192809126836.972412198
0.262412312.70796495131121.399841617
0.272447304.17941961135270.662959233
0.282482880.61898472138950.755052916
0.292518907.6183839141855.178557695
0.32555176.11226582143724.924792946
0.312591416.47316637144303.712434013
0.322627317.12426481143429.418473826
0.332662553.17704985141074.435119424
0.342696825.13178103137403.119041198
0.352729901.36117559132796.534455353
0.362761653.8237168127777.029755897
0.372792076.15662831122931.351379585
0.382821277.19479609118767.875873964
0.392849449.54614433115595.680428738
0.42876819.68519207113448.140532202
0.412903590.84888471112080.601666317
0.422929891.59766298111028.233732678
0.432955741.21093162109718.99497808
0.442981038.93310306107600.182666424
0.453005578.62710815104245.296184089
0.463029084.8139851699440.4000476857
0.473051261.5240142193208.4998888577
0.483071842.8941411485805.6570687569
0.493090634.7143871677656.756755007
0.53107539.1598985369253.1877711364
0.513122559.8673728861054.175292645
0.523135789.7574881453447.9553823041
0.533147387.8925657546672.3639312917
0.543157553.0918996640838.6383178217
0.553166500.9065203835965.6430742538
0.563174447.725556232008.5402051406
0.573181602.5647440928922.7172549937
0.583188164.6487582626656.6463269159
0.593194323.8314312825186.4512087891
0.63200261.1120254124471.5760549658
0.613206147.4733071224466.3908558605
0.623212140.4090604925102.9483233091
0.633218378.492502626268.9689438434
0.643224975.1236368227840.6868951498
0.653232013.2375275529664.545366885
0.663239543.140731331571.1699534691
0.673247585.4010472233436.6551964318
0.683256139.4607274135184.0437998645
0.693265196.4072212836792.6281161433
0.73274751.8600813338327.2855010558
0.713284813.4883369339872.1023209904
0.723295398.381791141469.1000542963
0.733306518.5602766343092.6816491654
0.743318157.2965872544584.2549865656
0.753330242.9000863245687.3120740224
0.763342628.6398660446097.5360943309
0.773355087.0015428945524.342181815
0.783367323.7619050543779.5384225444
0.793379012.960411440827.8917181761
0.83389848.1621195336834.8286763541
0.813399599.2472030532165.159800662
0.823408159.3606076427322.2769074695
0.833415566.6814673222846.3859001527
0.843421992.416224819190.274640119
0.853427698.3258987416599.2607947346
0.863432978.4190571215072.4300244
0.873438103.7043930314389.4462040557
0.883443284.6371952914241.5186408974
0.893448659.1653808514332.0461500764
0.93454312.9048918614458.1813200584
0.913460340.8744148114600.6756965913
0.923466959.0339751215038.051552683
0.933474682.1156315716374.5625293324
0.943484643.5339838819581.4832706342
0.953499134.367497326613.0080879621
0.963521850.5180219239812.9735001173
0.973556164.7682769555263.5343329975
0.983601183.4053056458423.2821375873
0.993649597.2988418647573.9382746435

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 1131410.62811349 & 191591.318860052 \tabularnewline
0.02 & 1295113.14863011 & 126214.760646417 \tabularnewline
0.03 & 1404133.65595745 & 109855.328250702 \tabularnewline
0.04 & 1486047.63184221 & 128280.232414164 \tabularnewline
0.05 & 1562286.71407804 & 140601.950858529 \tabularnewline
0.06 & 1633998.44047084 & 132451.660886695 \tabularnewline
0.07 & 1696028.84071601 & 112184.873635137 \tabularnewline
0.08 & 1746239.39289283 & 92800.8798809595 \tabularnewline
0.09 & 1786706.06506617 & 81716.1331103172 \tabularnewline
0.1 & 1821438.09519275 & 80333.9948923573 \tabularnewline
0.11 & 1854327.60740864 & 86988.0313667256 \tabularnewline
0.12 & 1888220.81831532 & 98742.9553019287 \tabularnewline
0.13 & 1924683.19088772 & 112176.302857399 \tabularnewline
0.14 & 1964058.24918 & 124067.07869198 \tabularnewline
0.15 & 2005708.96230456 & 132091.224353724 \tabularnewline
0.16 & 2048412.06956519 & 135281.842800775 \tabularnewline
0.17 & 2090816.52517025 & 134115.700867723 \tabularnewline
0.18 & 2131835.07417418 & 130074.161078623 \tabularnewline
0.19 & 2170869.09040329 & 125061.551779454 \tabularnewline
0.2 & 2207842.02639518 & 120766.879526014 \tabularnewline
0.21 & 2243086.06870912 & 118284.945061262 \tabularnewline
0.22 & 2277159.74311997 & 117993.946494257 \tabularnewline
0.23 & 2310669.38957569 & 119691.204270885 \tabularnewline
0.24 & 2344139.98982773 & 122846.911288477 \tabularnewline
0.25 & 2377948.97192809 & 126836.972412198 \tabularnewline
0.26 & 2412312.70796495 & 131121.399841617 \tabularnewline
0.27 & 2447304.17941961 & 135270.662959233 \tabularnewline
0.28 & 2482880.61898472 & 138950.755052916 \tabularnewline
0.29 & 2518907.6183839 & 141855.178557695 \tabularnewline
0.3 & 2555176.11226582 & 143724.924792946 \tabularnewline
0.31 & 2591416.47316637 & 144303.712434013 \tabularnewline
0.32 & 2627317.12426481 & 143429.418473826 \tabularnewline
0.33 & 2662553.17704985 & 141074.435119424 \tabularnewline
0.34 & 2696825.13178103 & 137403.119041198 \tabularnewline
0.35 & 2729901.36117559 & 132796.534455353 \tabularnewline
0.36 & 2761653.8237168 & 127777.029755897 \tabularnewline
0.37 & 2792076.15662831 & 122931.351379585 \tabularnewline
0.38 & 2821277.19479609 & 118767.875873964 \tabularnewline
0.39 & 2849449.54614433 & 115595.680428738 \tabularnewline
0.4 & 2876819.68519207 & 113448.140532202 \tabularnewline
0.41 & 2903590.84888471 & 112080.601666317 \tabularnewline
0.42 & 2929891.59766298 & 111028.233732678 \tabularnewline
0.43 & 2955741.21093162 & 109718.99497808 \tabularnewline
0.44 & 2981038.93310306 & 107600.182666424 \tabularnewline
0.45 & 3005578.62710815 & 104245.296184089 \tabularnewline
0.46 & 3029084.81398516 & 99440.4000476857 \tabularnewline
0.47 & 3051261.52401421 & 93208.4998888577 \tabularnewline
0.48 & 3071842.89414114 & 85805.6570687569 \tabularnewline
0.49 & 3090634.71438716 & 77656.756755007 \tabularnewline
0.5 & 3107539.15989853 & 69253.1877711364 \tabularnewline
0.51 & 3122559.86737288 & 61054.175292645 \tabularnewline
0.52 & 3135789.75748814 & 53447.9553823041 \tabularnewline
0.53 & 3147387.89256575 & 46672.3639312917 \tabularnewline
0.54 & 3157553.09189966 & 40838.6383178217 \tabularnewline
0.55 & 3166500.90652038 & 35965.6430742538 \tabularnewline
0.56 & 3174447.7255562 & 32008.5402051406 \tabularnewline
0.57 & 3181602.56474409 & 28922.7172549937 \tabularnewline
0.58 & 3188164.64875826 & 26656.6463269159 \tabularnewline
0.59 & 3194323.83143128 & 25186.4512087891 \tabularnewline
0.6 & 3200261.11202541 & 24471.5760549658 \tabularnewline
0.61 & 3206147.47330712 & 24466.3908558605 \tabularnewline
0.62 & 3212140.40906049 & 25102.9483233091 \tabularnewline
0.63 & 3218378.4925026 & 26268.9689438434 \tabularnewline
0.64 & 3224975.12363682 & 27840.6868951498 \tabularnewline
0.65 & 3232013.23752755 & 29664.545366885 \tabularnewline
0.66 & 3239543.1407313 & 31571.1699534691 \tabularnewline
0.67 & 3247585.40104722 & 33436.6551964318 \tabularnewline
0.68 & 3256139.46072741 & 35184.0437998645 \tabularnewline
0.69 & 3265196.40722128 & 36792.6281161433 \tabularnewline
0.7 & 3274751.86008133 & 38327.2855010558 \tabularnewline
0.71 & 3284813.48833693 & 39872.1023209904 \tabularnewline
0.72 & 3295398.3817911 & 41469.1000542963 \tabularnewline
0.73 & 3306518.56027663 & 43092.6816491654 \tabularnewline
0.74 & 3318157.29658725 & 44584.2549865656 \tabularnewline
0.75 & 3330242.90008632 & 45687.3120740224 \tabularnewline
0.76 & 3342628.63986604 & 46097.5360943309 \tabularnewline
0.77 & 3355087.00154289 & 45524.342181815 \tabularnewline
0.78 & 3367323.76190505 & 43779.5384225444 \tabularnewline
0.79 & 3379012.9604114 & 40827.8917181761 \tabularnewline
0.8 & 3389848.16211953 & 36834.8286763541 \tabularnewline
0.81 & 3399599.24720305 & 32165.159800662 \tabularnewline
0.82 & 3408159.36060764 & 27322.2769074695 \tabularnewline
0.83 & 3415566.68146732 & 22846.3859001527 \tabularnewline
0.84 & 3421992.4162248 & 19190.274640119 \tabularnewline
0.85 & 3427698.32589874 & 16599.2607947346 \tabularnewline
0.86 & 3432978.41905712 & 15072.4300244 \tabularnewline
0.87 & 3438103.70439303 & 14389.4462040557 \tabularnewline
0.88 & 3443284.63719529 & 14241.5186408974 \tabularnewline
0.89 & 3448659.16538085 & 14332.0461500764 \tabularnewline
0.9 & 3454312.90489186 & 14458.1813200584 \tabularnewline
0.91 & 3460340.87441481 & 14600.6756965913 \tabularnewline
0.92 & 3466959.03397512 & 15038.051552683 \tabularnewline
0.93 & 3474682.11563157 & 16374.5625293324 \tabularnewline
0.94 & 3484643.53398388 & 19581.4832706342 \tabularnewline
0.95 & 3499134.3674973 & 26613.0080879621 \tabularnewline
0.96 & 3521850.51802192 & 39812.9735001173 \tabularnewline
0.97 & 3556164.76827695 & 55263.5343329975 \tabularnewline
0.98 & 3601183.40530564 & 58423.2821375873 \tabularnewline
0.99 & 3649597.29884186 & 47573.9382746435 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279893&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]1131410.62811349[/C][C]191591.318860052[/C][/ROW]
[ROW][C]0.02[/C][C]1295113.14863011[/C][C]126214.760646417[/C][/ROW]
[ROW][C]0.03[/C][C]1404133.65595745[/C][C]109855.328250702[/C][/ROW]
[ROW][C]0.04[/C][C]1486047.63184221[/C][C]128280.232414164[/C][/ROW]
[ROW][C]0.05[/C][C]1562286.71407804[/C][C]140601.950858529[/C][/ROW]
[ROW][C]0.06[/C][C]1633998.44047084[/C][C]132451.660886695[/C][/ROW]
[ROW][C]0.07[/C][C]1696028.84071601[/C][C]112184.873635137[/C][/ROW]
[ROW][C]0.08[/C][C]1746239.39289283[/C][C]92800.8798809595[/C][/ROW]
[ROW][C]0.09[/C][C]1786706.06506617[/C][C]81716.1331103172[/C][/ROW]
[ROW][C]0.1[/C][C]1821438.09519275[/C][C]80333.9948923573[/C][/ROW]
[ROW][C]0.11[/C][C]1854327.60740864[/C][C]86988.0313667256[/C][/ROW]
[ROW][C]0.12[/C][C]1888220.81831532[/C][C]98742.9553019287[/C][/ROW]
[ROW][C]0.13[/C][C]1924683.19088772[/C][C]112176.302857399[/C][/ROW]
[ROW][C]0.14[/C][C]1964058.24918[/C][C]124067.07869198[/C][/ROW]
[ROW][C]0.15[/C][C]2005708.96230456[/C][C]132091.224353724[/C][/ROW]
[ROW][C]0.16[/C][C]2048412.06956519[/C][C]135281.842800775[/C][/ROW]
[ROW][C]0.17[/C][C]2090816.52517025[/C][C]134115.700867723[/C][/ROW]
[ROW][C]0.18[/C][C]2131835.07417418[/C][C]130074.161078623[/C][/ROW]
[ROW][C]0.19[/C][C]2170869.09040329[/C][C]125061.551779454[/C][/ROW]
[ROW][C]0.2[/C][C]2207842.02639518[/C][C]120766.879526014[/C][/ROW]
[ROW][C]0.21[/C][C]2243086.06870912[/C][C]118284.945061262[/C][/ROW]
[ROW][C]0.22[/C][C]2277159.74311997[/C][C]117993.946494257[/C][/ROW]
[ROW][C]0.23[/C][C]2310669.38957569[/C][C]119691.204270885[/C][/ROW]
[ROW][C]0.24[/C][C]2344139.98982773[/C][C]122846.911288477[/C][/ROW]
[ROW][C]0.25[/C][C]2377948.97192809[/C][C]126836.972412198[/C][/ROW]
[ROW][C]0.26[/C][C]2412312.70796495[/C][C]131121.399841617[/C][/ROW]
[ROW][C]0.27[/C][C]2447304.17941961[/C][C]135270.662959233[/C][/ROW]
[ROW][C]0.28[/C][C]2482880.61898472[/C][C]138950.755052916[/C][/ROW]
[ROW][C]0.29[/C][C]2518907.6183839[/C][C]141855.178557695[/C][/ROW]
[ROW][C]0.3[/C][C]2555176.11226582[/C][C]143724.924792946[/C][/ROW]
[ROW][C]0.31[/C][C]2591416.47316637[/C][C]144303.712434013[/C][/ROW]
[ROW][C]0.32[/C][C]2627317.12426481[/C][C]143429.418473826[/C][/ROW]
[ROW][C]0.33[/C][C]2662553.17704985[/C][C]141074.435119424[/C][/ROW]
[ROW][C]0.34[/C][C]2696825.13178103[/C][C]137403.119041198[/C][/ROW]
[ROW][C]0.35[/C][C]2729901.36117559[/C][C]132796.534455353[/C][/ROW]
[ROW][C]0.36[/C][C]2761653.8237168[/C][C]127777.029755897[/C][/ROW]
[ROW][C]0.37[/C][C]2792076.15662831[/C][C]122931.351379585[/C][/ROW]
[ROW][C]0.38[/C][C]2821277.19479609[/C][C]118767.875873964[/C][/ROW]
[ROW][C]0.39[/C][C]2849449.54614433[/C][C]115595.680428738[/C][/ROW]
[ROW][C]0.4[/C][C]2876819.68519207[/C][C]113448.140532202[/C][/ROW]
[ROW][C]0.41[/C][C]2903590.84888471[/C][C]112080.601666317[/C][/ROW]
[ROW][C]0.42[/C][C]2929891.59766298[/C][C]111028.233732678[/C][/ROW]
[ROW][C]0.43[/C][C]2955741.21093162[/C][C]109718.99497808[/C][/ROW]
[ROW][C]0.44[/C][C]2981038.93310306[/C][C]107600.182666424[/C][/ROW]
[ROW][C]0.45[/C][C]3005578.62710815[/C][C]104245.296184089[/C][/ROW]
[ROW][C]0.46[/C][C]3029084.81398516[/C][C]99440.4000476857[/C][/ROW]
[ROW][C]0.47[/C][C]3051261.52401421[/C][C]93208.4998888577[/C][/ROW]
[ROW][C]0.48[/C][C]3071842.89414114[/C][C]85805.6570687569[/C][/ROW]
[ROW][C]0.49[/C][C]3090634.71438716[/C][C]77656.756755007[/C][/ROW]
[ROW][C]0.5[/C][C]3107539.15989853[/C][C]69253.1877711364[/C][/ROW]
[ROW][C]0.51[/C][C]3122559.86737288[/C][C]61054.175292645[/C][/ROW]
[ROW][C]0.52[/C][C]3135789.75748814[/C][C]53447.9553823041[/C][/ROW]
[ROW][C]0.53[/C][C]3147387.89256575[/C][C]46672.3639312917[/C][/ROW]
[ROW][C]0.54[/C][C]3157553.09189966[/C][C]40838.6383178217[/C][/ROW]
[ROW][C]0.55[/C][C]3166500.90652038[/C][C]35965.6430742538[/C][/ROW]
[ROW][C]0.56[/C][C]3174447.7255562[/C][C]32008.5402051406[/C][/ROW]
[ROW][C]0.57[/C][C]3181602.56474409[/C][C]28922.7172549937[/C][/ROW]
[ROW][C]0.58[/C][C]3188164.64875826[/C][C]26656.6463269159[/C][/ROW]
[ROW][C]0.59[/C][C]3194323.83143128[/C][C]25186.4512087891[/C][/ROW]
[ROW][C]0.6[/C][C]3200261.11202541[/C][C]24471.5760549658[/C][/ROW]
[ROW][C]0.61[/C][C]3206147.47330712[/C][C]24466.3908558605[/C][/ROW]
[ROW][C]0.62[/C][C]3212140.40906049[/C][C]25102.9483233091[/C][/ROW]
[ROW][C]0.63[/C][C]3218378.4925026[/C][C]26268.9689438434[/C][/ROW]
[ROW][C]0.64[/C][C]3224975.12363682[/C][C]27840.6868951498[/C][/ROW]
[ROW][C]0.65[/C][C]3232013.23752755[/C][C]29664.545366885[/C][/ROW]
[ROW][C]0.66[/C][C]3239543.1407313[/C][C]31571.1699534691[/C][/ROW]
[ROW][C]0.67[/C][C]3247585.40104722[/C][C]33436.6551964318[/C][/ROW]
[ROW][C]0.68[/C][C]3256139.46072741[/C][C]35184.0437998645[/C][/ROW]
[ROW][C]0.69[/C][C]3265196.40722128[/C][C]36792.6281161433[/C][/ROW]
[ROW][C]0.7[/C][C]3274751.86008133[/C][C]38327.2855010558[/C][/ROW]
[ROW][C]0.71[/C][C]3284813.48833693[/C][C]39872.1023209904[/C][/ROW]
[ROW][C]0.72[/C][C]3295398.3817911[/C][C]41469.1000542963[/C][/ROW]
[ROW][C]0.73[/C][C]3306518.56027663[/C][C]43092.6816491654[/C][/ROW]
[ROW][C]0.74[/C][C]3318157.29658725[/C][C]44584.2549865656[/C][/ROW]
[ROW][C]0.75[/C][C]3330242.90008632[/C][C]45687.3120740224[/C][/ROW]
[ROW][C]0.76[/C][C]3342628.63986604[/C][C]46097.5360943309[/C][/ROW]
[ROW][C]0.77[/C][C]3355087.00154289[/C][C]45524.342181815[/C][/ROW]
[ROW][C]0.78[/C][C]3367323.76190505[/C][C]43779.5384225444[/C][/ROW]
[ROW][C]0.79[/C][C]3379012.9604114[/C][C]40827.8917181761[/C][/ROW]
[ROW][C]0.8[/C][C]3389848.16211953[/C][C]36834.8286763541[/C][/ROW]
[ROW][C]0.81[/C][C]3399599.24720305[/C][C]32165.159800662[/C][/ROW]
[ROW][C]0.82[/C][C]3408159.36060764[/C][C]27322.2769074695[/C][/ROW]
[ROW][C]0.83[/C][C]3415566.68146732[/C][C]22846.3859001527[/C][/ROW]
[ROW][C]0.84[/C][C]3421992.4162248[/C][C]19190.274640119[/C][/ROW]
[ROW][C]0.85[/C][C]3427698.32589874[/C][C]16599.2607947346[/C][/ROW]
[ROW][C]0.86[/C][C]3432978.41905712[/C][C]15072.4300244[/C][/ROW]
[ROW][C]0.87[/C][C]3438103.70439303[/C][C]14389.4462040557[/C][/ROW]
[ROW][C]0.88[/C][C]3443284.63719529[/C][C]14241.5186408974[/C][/ROW]
[ROW][C]0.89[/C][C]3448659.16538085[/C][C]14332.0461500764[/C][/ROW]
[ROW][C]0.9[/C][C]3454312.90489186[/C][C]14458.1813200584[/C][/ROW]
[ROW][C]0.91[/C][C]3460340.87441481[/C][C]14600.6756965913[/C][/ROW]
[ROW][C]0.92[/C][C]3466959.03397512[/C][C]15038.051552683[/C][/ROW]
[ROW][C]0.93[/C][C]3474682.11563157[/C][C]16374.5625293324[/C][/ROW]
[ROW][C]0.94[/C][C]3484643.53398388[/C][C]19581.4832706342[/C][/ROW]
[ROW][C]0.95[/C][C]3499134.3674973[/C][C]26613.0080879621[/C][/ROW]
[ROW][C]0.96[/C][C]3521850.51802192[/C][C]39812.9735001173[/C][/ROW]
[ROW][C]0.97[/C][C]3556164.76827695[/C][C]55263.5343329975[/C][/ROW]
[ROW][C]0.98[/C][C]3601183.40530564[/C][C]58423.2821375873[/C][/ROW]
[ROW][C]0.99[/C][C]3649597.29884186[/C][C]47573.9382746435[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279893&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279893&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
0.011131410.62811349191591.318860052
0.021295113.14863011126214.760646417
0.031404133.65595745109855.328250702
0.041486047.63184221128280.232414164
0.051562286.71407804140601.950858529
0.061633998.44047084132451.660886695
0.071696028.84071601112184.873635137
0.081746239.3928928392800.8798809595
0.091786706.0650661781716.1331103172
0.11821438.0951927580333.9948923573
0.111854327.6074086486988.0313667256
0.121888220.8183153298742.9553019287
0.131924683.19088772112176.302857399
0.141964058.24918124067.07869198
0.152005708.96230456132091.224353724
0.162048412.06956519135281.842800775
0.172090816.52517025134115.700867723
0.182131835.07417418130074.161078623
0.192170869.09040329125061.551779454
0.22207842.02639518120766.879526014
0.212243086.06870912118284.945061262
0.222277159.74311997117993.946494257
0.232310669.38957569119691.204270885
0.242344139.98982773122846.911288477
0.252377948.97192809126836.972412198
0.262412312.70796495131121.399841617
0.272447304.17941961135270.662959233
0.282482880.61898472138950.755052916
0.292518907.6183839141855.178557695
0.32555176.11226582143724.924792946
0.312591416.47316637144303.712434013
0.322627317.12426481143429.418473826
0.332662553.17704985141074.435119424
0.342696825.13178103137403.119041198
0.352729901.36117559132796.534455353
0.362761653.8237168127777.029755897
0.372792076.15662831122931.351379585
0.382821277.19479609118767.875873964
0.392849449.54614433115595.680428738
0.42876819.68519207113448.140532202
0.412903590.84888471112080.601666317
0.422929891.59766298111028.233732678
0.432955741.21093162109718.99497808
0.442981038.93310306107600.182666424
0.453005578.62710815104245.296184089
0.463029084.8139851699440.4000476857
0.473051261.5240142193208.4998888577
0.483071842.8941411485805.6570687569
0.493090634.7143871677656.756755007
0.53107539.1598985369253.1877711364
0.513122559.8673728861054.175292645
0.523135789.7574881453447.9553823041
0.533147387.8925657546672.3639312917
0.543157553.0918996640838.6383178217
0.553166500.9065203835965.6430742538
0.563174447.725556232008.5402051406
0.573181602.5647440928922.7172549937
0.583188164.6487582626656.6463269159
0.593194323.8314312825186.4512087891
0.63200261.1120254124471.5760549658
0.613206147.4733071224466.3908558605
0.623212140.4090604925102.9483233091
0.633218378.492502626268.9689438434
0.643224975.1236368227840.6868951498
0.653232013.2375275529664.545366885
0.663239543.140731331571.1699534691
0.673247585.4010472233436.6551964318
0.683256139.4607274135184.0437998645
0.693265196.4072212836792.6281161433
0.73274751.8600813338327.2855010558
0.713284813.4883369339872.1023209904
0.723295398.381791141469.1000542963
0.733306518.5602766343092.6816491654
0.743318157.2965872544584.2549865656
0.753330242.9000863245687.3120740224
0.763342628.6398660446097.5360943309
0.773355087.0015428945524.342181815
0.783367323.7619050543779.5384225444
0.793379012.960411440827.8917181761
0.83389848.1621195336834.8286763541
0.813399599.2472030532165.159800662
0.823408159.3606076427322.2769074695
0.833415566.6814673222846.3859001527
0.843421992.416224819190.274640119
0.853427698.3258987416599.2607947346
0.863432978.4190571215072.4300244
0.873438103.7043930314389.4462040557
0.883443284.6371952914241.5186408974
0.893448659.1653808514332.0461500764
0.93454312.9048918614458.1813200584
0.913460340.8744148114600.6756965913
0.923466959.0339751215038.051552683
0.933474682.1156315716374.5625293324
0.943484643.5339838819581.4832706342
0.953499134.367497326613.0080879621
0.963521850.5180219239812.9735001173
0.973556164.7682769555263.5343329975
0.983601183.4053056458423.2821375873
0.993649597.2988418647573.9382746435


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')