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Description of Statistical Computation

Author's title

Percentielen - Koers BEL 20 van Januari 2000 tot Januari 2009 - Claus Wesle...

Author*Unverified author*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationMon, 09 Mar 2009 02:20:52 -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/Mar/09/t1236586946cukd57lgmmvyemm.htm/, Retrieved Sun, 28 Apr 2024 21:40:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=38732, Retrieved Sun, 28 Apr 2024 21:40:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145

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 - Ko...] [2009-03-09 08:20:52] [fbcf875f1b36dfb87c2c6a55976f6e7b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3030.29
2803.47
2767.63
2882.6
2863.36
2897.06
3012.61
3142.95
3032.93
3045.78
3110.52
3013.24
2987.1
2995.55
2833.18
2848.96
2794.83
2845.26
2915.02
2892.63
2604.42
2641.65
2659.81
2638.53
2720.25
2745.88
2735.7
2811.7
2799.43
2555.28
2304.98
2214.95
2065.81
1940.49
2042
1995.37
1946.81
1765.9
1635.25
1833.42
1910.43
1959.67
1969.6
2061.41
2091.48
2120.88
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.6
2452.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41

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=38732&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=38732&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38732&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
0.011701.93265653004100.582434261679
0.021781.9743535877872.9101669870397
0.031839.6656118685756.8071684522096
0.041878.3766637357847.4756168636868
0.051906.4919149690542.1377677697821
0.061929.0360083630140.2483974254041
0.071948.9214897993241.6471277800749
0.081968.0248343930945.64360915163
0.091987.5336166792451.2227917849916
0.12008.1149923418457.579192040343
0.112030.0987465082464.4091968402876
0.122053.6586976082671.788886150084
0.132078.9310537920579.8647250570861
0.142106.0426333663488.5635230847175
0.152135.0703628716797.548714531636
0.162165.97632135944106.247422634124
0.172198.55695439528113.946284896731
0.182232.42910978321119.935180754252
0.192267.06217267112123.652638404518
0.22301.85404578057124.926122894040
0.212336.23471802647124.038949452975
0.222369.76752452502121.737357047554
0.232402.21399335506118.946922846192
0.242433.53946112043116.507946166065
0.252463.85965722726114.855076281518
0.262493.35149007588113.933086478070
0.272522.16267760546113.307715048729
0.282550.35030436246112.407756729121
0.292577.86233775718110.752381708623
0.32604.55791145626108.075450869571
0.312630.25008495120104.348803356909
0.322654.7522160951399.7297836058729
0.332677.9142217249394.4722693098363
0.342699.6432212883888.8553944950537
0.352719.9099731104183.1531205852498
0.362738.7459142440477.6128673228728
0.372756.235677680272.4477471313229
0.382772.5082182748667.8511039225062
0.392787.7277401359963.9718797750802
0.42802.0843841588160.9328213264314
0.412815.7842169763858.7920225476337
0.422829.0381528403257.5853409867148
0.432842.0497236165757.2476548311654
0.442855.0019695983857.6753395923632
0.452868.0441835619858.6765110975473
0.462881.2798154694160.0217538431182
0.472894.75741039561.431256495028
0.482908.4667476837962.6072732496425
0.492922.3420991594363.313135182173
0.52936.2735960847163.3483126543476
0.512950.1262110043162.6499082025699
0.522963.7642012500761.2632011042319
0.532977.0775469831459.3754235449126
0.542990.0064190700157.2660976195527
0.553002.5602582313255.3046929029391
0.563014.8295042487953.9042985231073
0.573026.9899019855353.4702401239847
0.583039.3009473706454.367086212576
0.593052.1007773438656.9282526783811
0.63065.7993029333861.4300083876444
0.613080.8697560946668.1045803599223
0.623097.8366828441477.0979011868192
0.633117.2567017181988.4793042677523
0.643139.68798651471102.133993332618
0.653165.64598463054117.731188424693
0.663195.54627854572134.674080638947
0.673229.63999824634152.088470328748
0.683267.95156740776168.872956208584
0.693310.23142653848183.781132618344
0.73355.93654460102195.591712018358
0.713404.24839296857203.239411264178
0.723454.13186143148206.021229503589
0.733504.43062773162203.711589528912
0.743553.98692144398196.604906678580
0.753601.76886017484185.528199590764
0.763646.98811240573171.697622284529
0.773689.19411080846156.618835960735
0.783728.33573736428141.910632547306
0.793764.78374583866129.183430934504
0.83799.30536760909119.905782839018
0.813832.97917466026115.158206019635
0.823867.04067143031115.284314405635
0.833902.66533412223119.581969231106
0.843940.72712762581126.27675158538
0.853981.60450478022133.021353498892
0.864025.11788566334137.609892301398
0.874070.64975427127138.722014147912
0.884117.42088173899136.355145198103
0.894164.80872097164131.682940077135
0.94212.55346783858126.32459930823
0.914260.74617365867121.391024797290
0.924309.62091391532116.862595400492
0.934359.29592600839111.834470597825
0.944409.60291878406105.332831434325
0.954459.9923211564496.7687312016468
0.964509.5229973865585.3410174489278
0.974557.6002709853170.527877110249
0.984606.18911163357.1204092503026
0.994657.8872638308459.5389245298498

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 1701.93265653004 & 100.582434261679 \tabularnewline
0.02 & 1781.97435358778 & 72.9101669870397 \tabularnewline
0.03 & 1839.66561186857 & 56.8071684522096 \tabularnewline
0.04 & 1878.37666373578 & 47.4756168636868 \tabularnewline
0.05 & 1906.49191496905 & 42.1377677697821 \tabularnewline
0.06 & 1929.03600836301 & 40.2483974254041 \tabularnewline
0.07 & 1948.92148979932 & 41.6471277800749 \tabularnewline
0.08 & 1968.02483439309 & 45.64360915163 \tabularnewline
0.09 & 1987.53361667924 & 51.2227917849916 \tabularnewline
0.1 & 2008.11499234184 & 57.579192040343 \tabularnewline
0.11 & 2030.09874650824 & 64.4091968402876 \tabularnewline
0.12 & 2053.65869760826 & 71.788886150084 \tabularnewline
0.13 & 2078.93105379205 & 79.8647250570861 \tabularnewline
0.14 & 2106.04263336634 & 88.5635230847175 \tabularnewline
0.15 & 2135.07036287167 & 97.548714531636 \tabularnewline
0.16 & 2165.97632135944 & 106.247422634124 \tabularnewline
0.17 & 2198.55695439528 & 113.946284896731 \tabularnewline
0.18 & 2232.42910978321 & 119.935180754252 \tabularnewline
0.19 & 2267.06217267112 & 123.652638404518 \tabularnewline
0.2 & 2301.85404578057 & 124.926122894040 \tabularnewline
0.21 & 2336.23471802647 & 124.038949452975 \tabularnewline
0.22 & 2369.76752452502 & 121.737357047554 \tabularnewline
0.23 & 2402.21399335506 & 118.946922846192 \tabularnewline
0.24 & 2433.53946112043 & 116.507946166065 \tabularnewline
0.25 & 2463.85965722726 & 114.855076281518 \tabularnewline
0.26 & 2493.35149007588 & 113.933086478070 \tabularnewline
0.27 & 2522.16267760546 & 113.307715048729 \tabularnewline
0.28 & 2550.35030436246 & 112.407756729121 \tabularnewline
0.29 & 2577.86233775718 & 110.752381708623 \tabularnewline
0.3 & 2604.55791145626 & 108.075450869571 \tabularnewline
0.31 & 2630.25008495120 & 104.348803356909 \tabularnewline
0.32 & 2654.75221609513 & 99.7297836058729 \tabularnewline
0.33 & 2677.91422172493 & 94.4722693098363 \tabularnewline
0.34 & 2699.64322128838 & 88.8553944950537 \tabularnewline
0.35 & 2719.90997311041 & 83.1531205852498 \tabularnewline
0.36 & 2738.74591424404 & 77.6128673228728 \tabularnewline
0.37 & 2756.2356776802 & 72.4477471313229 \tabularnewline
0.38 & 2772.50821827486 & 67.8511039225062 \tabularnewline
0.39 & 2787.72774013599 & 63.9718797750802 \tabularnewline
0.4 & 2802.08438415881 & 60.9328213264314 \tabularnewline
0.41 & 2815.78421697638 & 58.7920225476337 \tabularnewline
0.42 & 2829.03815284032 & 57.5853409867148 \tabularnewline
0.43 & 2842.04972361657 & 57.2476548311654 \tabularnewline
0.44 & 2855.00196959838 & 57.6753395923632 \tabularnewline
0.45 & 2868.04418356198 & 58.6765110975473 \tabularnewline
0.46 & 2881.27981546941 & 60.0217538431182 \tabularnewline
0.47 & 2894.757410395 & 61.431256495028 \tabularnewline
0.48 & 2908.46674768379 & 62.6072732496425 \tabularnewline
0.49 & 2922.34209915943 & 63.313135182173 \tabularnewline
0.5 & 2936.27359608471 & 63.3483126543476 \tabularnewline
0.51 & 2950.12621100431 & 62.6499082025699 \tabularnewline
0.52 & 2963.76420125007 & 61.2632011042319 \tabularnewline
0.53 & 2977.07754698314 & 59.3754235449126 \tabularnewline
0.54 & 2990.00641907001 & 57.2660976195527 \tabularnewline
0.55 & 3002.56025823132 & 55.3046929029391 \tabularnewline
0.56 & 3014.82950424879 & 53.9042985231073 \tabularnewline
0.57 & 3026.98990198553 & 53.4702401239847 \tabularnewline
0.58 & 3039.30094737064 & 54.367086212576 \tabularnewline
0.59 & 3052.10077734386 & 56.9282526783811 \tabularnewline
0.6 & 3065.79930293338 & 61.4300083876444 \tabularnewline
0.61 & 3080.86975609466 & 68.1045803599223 \tabularnewline
0.62 & 3097.83668284414 & 77.0979011868192 \tabularnewline
0.63 & 3117.25670171819 & 88.4793042677523 \tabularnewline
0.64 & 3139.68798651471 & 102.133993332618 \tabularnewline
0.65 & 3165.64598463054 & 117.731188424693 \tabularnewline
0.66 & 3195.54627854572 & 134.674080638947 \tabularnewline
0.67 & 3229.63999824634 & 152.088470328748 \tabularnewline
0.68 & 3267.95156740776 & 168.872956208584 \tabularnewline
0.69 & 3310.23142653848 & 183.781132618344 \tabularnewline
0.7 & 3355.93654460102 & 195.591712018358 \tabularnewline
0.71 & 3404.24839296857 & 203.239411264178 \tabularnewline
0.72 & 3454.13186143148 & 206.021229503589 \tabularnewline
0.73 & 3504.43062773162 & 203.711589528912 \tabularnewline
0.74 & 3553.98692144398 & 196.604906678580 \tabularnewline
0.75 & 3601.76886017484 & 185.528199590764 \tabularnewline
0.76 & 3646.98811240573 & 171.697622284529 \tabularnewline
0.77 & 3689.19411080846 & 156.618835960735 \tabularnewline
0.78 & 3728.33573736428 & 141.910632547306 \tabularnewline
0.79 & 3764.78374583866 & 129.183430934504 \tabularnewline
0.8 & 3799.30536760909 & 119.905782839018 \tabularnewline
0.81 & 3832.97917466026 & 115.158206019635 \tabularnewline
0.82 & 3867.04067143031 & 115.284314405635 \tabularnewline
0.83 & 3902.66533412223 & 119.581969231106 \tabularnewline
0.84 & 3940.72712762581 & 126.27675158538 \tabularnewline
0.85 & 3981.60450478022 & 133.021353498892 \tabularnewline
0.86 & 4025.11788566334 & 137.609892301398 \tabularnewline
0.87 & 4070.64975427127 & 138.722014147912 \tabularnewline
0.88 & 4117.42088173899 & 136.355145198103 \tabularnewline
0.89 & 4164.80872097164 & 131.682940077135 \tabularnewline
0.9 & 4212.55346783858 & 126.32459930823 \tabularnewline
0.91 & 4260.74617365867 & 121.391024797290 \tabularnewline
0.92 & 4309.62091391532 & 116.862595400492 \tabularnewline
0.93 & 4359.29592600839 & 111.834470597825 \tabularnewline
0.94 & 4409.60291878406 & 105.332831434325 \tabularnewline
0.95 & 4459.99232115644 & 96.7687312016468 \tabularnewline
0.96 & 4509.52299738655 & 85.3410174489278 \tabularnewline
0.97 & 4557.60027098531 & 70.527877110249 \tabularnewline
0.98 & 4606.189111633 & 57.1204092503026 \tabularnewline
0.99 & 4657.88726383084 & 59.5389245298498 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=38732&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]1701.93265653004[/C][C]100.582434261679[/C][/ROW]
[ROW][C]0.02[/C][C]1781.97435358778[/C][C]72.9101669870397[/C][/ROW]
[ROW][C]0.03[/C][C]1839.66561186857[/C][C]56.8071684522096[/C][/ROW]
[ROW][C]0.04[/C][C]1878.37666373578[/C][C]47.4756168636868[/C][/ROW]
[ROW][C]0.05[/C][C]1906.49191496905[/C][C]42.1377677697821[/C][/ROW]
[ROW][C]0.06[/C][C]1929.03600836301[/C][C]40.2483974254041[/C][/ROW]
[ROW][C]0.07[/C][C]1948.92148979932[/C][C]41.6471277800749[/C][/ROW]
[ROW][C]0.08[/C][C]1968.02483439309[/C][C]45.64360915163[/C][/ROW]
[ROW][C]0.09[/C][C]1987.53361667924[/C][C]51.2227917849916[/C][/ROW]
[ROW][C]0.1[/C][C]2008.11499234184[/C][C]57.579192040343[/C][/ROW]
[ROW][C]0.11[/C][C]2030.09874650824[/C][C]64.4091968402876[/C][/ROW]
[ROW][C]0.12[/C][C]2053.65869760826[/C][C]71.788886150084[/C][/ROW]
[ROW][C]0.13[/C][C]2078.93105379205[/C][C]79.8647250570861[/C][/ROW]
[ROW][C]0.14[/C][C]2106.04263336634[/C][C]88.5635230847175[/C][/ROW]
[ROW][C]0.15[/C][C]2135.07036287167[/C][C]97.548714531636[/C][/ROW]
[ROW][C]0.16[/C][C]2165.97632135944[/C][C]106.247422634124[/C][/ROW]
[ROW][C]0.17[/C][C]2198.55695439528[/C][C]113.946284896731[/C][/ROW]
[ROW][C]0.18[/C][C]2232.42910978321[/C][C]119.935180754252[/C][/ROW]
[ROW][C]0.19[/C][C]2267.06217267112[/C][C]123.652638404518[/C][/ROW]
[ROW][C]0.2[/C][C]2301.85404578057[/C][C]124.926122894040[/C][/ROW]
[ROW][C]0.21[/C][C]2336.23471802647[/C][C]124.038949452975[/C][/ROW]
[ROW][C]0.22[/C][C]2369.76752452502[/C][C]121.737357047554[/C][/ROW]
[ROW][C]0.23[/C][C]2402.21399335506[/C][C]118.946922846192[/C][/ROW]
[ROW][C]0.24[/C][C]2433.53946112043[/C][C]116.507946166065[/C][/ROW]
[ROW][C]0.25[/C][C]2463.85965722726[/C][C]114.855076281518[/C][/ROW]
[ROW][C]0.26[/C][C]2493.35149007588[/C][C]113.933086478070[/C][/ROW]
[ROW][C]0.27[/C][C]2522.16267760546[/C][C]113.307715048729[/C][/ROW]
[ROW][C]0.28[/C][C]2550.35030436246[/C][C]112.407756729121[/C][/ROW]
[ROW][C]0.29[/C][C]2577.86233775718[/C][C]110.752381708623[/C][/ROW]
[ROW][C]0.3[/C][C]2604.55791145626[/C][C]108.075450869571[/C][/ROW]
[ROW][C]0.31[/C][C]2630.25008495120[/C][C]104.348803356909[/C][/ROW]
[ROW][C]0.32[/C][C]2654.75221609513[/C][C]99.7297836058729[/C][/ROW]
[ROW][C]0.33[/C][C]2677.91422172493[/C][C]94.4722693098363[/C][/ROW]
[ROW][C]0.34[/C][C]2699.64322128838[/C][C]88.8553944950537[/C][/ROW]
[ROW][C]0.35[/C][C]2719.90997311041[/C][C]83.1531205852498[/C][/ROW]
[ROW][C]0.36[/C][C]2738.74591424404[/C][C]77.6128673228728[/C][/ROW]
[ROW][C]0.37[/C][C]2756.2356776802[/C][C]72.4477471313229[/C][/ROW]
[ROW][C]0.38[/C][C]2772.50821827486[/C][C]67.8511039225062[/C][/ROW]
[ROW][C]0.39[/C][C]2787.72774013599[/C][C]63.9718797750802[/C][/ROW]
[ROW][C]0.4[/C][C]2802.08438415881[/C][C]60.9328213264314[/C][/ROW]
[ROW][C]0.41[/C][C]2815.78421697638[/C][C]58.7920225476337[/C][/ROW]
[ROW][C]0.42[/C][C]2829.03815284032[/C][C]57.5853409867148[/C][/ROW]
[ROW][C]0.43[/C][C]2842.04972361657[/C][C]57.2476548311654[/C][/ROW]
[ROW][C]0.44[/C][C]2855.00196959838[/C][C]57.6753395923632[/C][/ROW]
[ROW][C]0.45[/C][C]2868.04418356198[/C][C]58.6765110975473[/C][/ROW]
[ROW][C]0.46[/C][C]2881.27981546941[/C][C]60.0217538431182[/C][/ROW]
[ROW][C]0.47[/C][C]2894.757410395[/C][C]61.431256495028[/C][/ROW]
[ROW][C]0.48[/C][C]2908.46674768379[/C][C]62.6072732496425[/C][/ROW]
[ROW][C]0.49[/C][C]2922.34209915943[/C][C]63.313135182173[/C][/ROW]
[ROW][C]0.5[/C][C]2936.27359608471[/C][C]63.3483126543476[/C][/ROW]
[ROW][C]0.51[/C][C]2950.12621100431[/C][C]62.6499082025699[/C][/ROW]
[ROW][C]0.52[/C][C]2963.76420125007[/C][C]61.2632011042319[/C][/ROW]
[ROW][C]0.53[/C][C]2977.07754698314[/C][C]59.3754235449126[/C][/ROW]
[ROW][C]0.54[/C][C]2990.00641907001[/C][C]57.2660976195527[/C][/ROW]
[ROW][C]0.55[/C][C]3002.56025823132[/C][C]55.3046929029391[/C][/ROW]
[ROW][C]0.56[/C][C]3014.82950424879[/C][C]53.9042985231073[/C][/ROW]
[ROW][C]0.57[/C][C]3026.98990198553[/C][C]53.4702401239847[/C][/ROW]
[ROW][C]0.58[/C][C]3039.30094737064[/C][C]54.367086212576[/C][/ROW]
[ROW][C]0.59[/C][C]3052.10077734386[/C][C]56.9282526783811[/C][/ROW]
[ROW][C]0.6[/C][C]3065.79930293338[/C][C]61.4300083876444[/C][/ROW]
[ROW][C]0.61[/C][C]3080.86975609466[/C][C]68.1045803599223[/C][/ROW]
[ROW][C]0.62[/C][C]3097.83668284414[/C][C]77.0979011868192[/C][/ROW]
[ROW][C]0.63[/C][C]3117.25670171819[/C][C]88.4793042677523[/C][/ROW]
[ROW][C]0.64[/C][C]3139.68798651471[/C][C]102.133993332618[/C][/ROW]
[ROW][C]0.65[/C][C]3165.64598463054[/C][C]117.731188424693[/C][/ROW]
[ROW][C]0.66[/C][C]3195.54627854572[/C][C]134.674080638947[/C][/ROW]
[ROW][C]0.67[/C][C]3229.63999824634[/C][C]152.088470328748[/C][/ROW]
[ROW][C]0.68[/C][C]3267.95156740776[/C][C]168.872956208584[/C][/ROW]
[ROW][C]0.69[/C][C]3310.23142653848[/C][C]183.781132618344[/C][/ROW]
[ROW][C]0.7[/C][C]3355.93654460102[/C][C]195.591712018358[/C][/ROW]
[ROW][C]0.71[/C][C]3404.24839296857[/C][C]203.239411264178[/C][/ROW]
[ROW][C]0.72[/C][C]3454.13186143148[/C][C]206.021229503589[/C][/ROW]
[ROW][C]0.73[/C][C]3504.43062773162[/C][C]203.711589528912[/C][/ROW]
[ROW][C]0.74[/C][C]3553.98692144398[/C][C]196.604906678580[/C][/ROW]
[ROW][C]0.75[/C][C]3601.76886017484[/C][C]185.528199590764[/C][/ROW]
[ROW][C]0.76[/C][C]3646.98811240573[/C][C]171.697622284529[/C][/ROW]
[ROW][C]0.77[/C][C]3689.19411080846[/C][C]156.618835960735[/C][/ROW]
[ROW][C]0.78[/C][C]3728.33573736428[/C][C]141.910632547306[/C][/ROW]
[ROW][C]0.79[/C][C]3764.78374583866[/C][C]129.183430934504[/C][/ROW]
[ROW][C]0.8[/C][C]3799.30536760909[/C][C]119.905782839018[/C][/ROW]
[ROW][C]0.81[/C][C]3832.97917466026[/C][C]115.158206019635[/C][/ROW]
[ROW][C]0.82[/C][C]3867.04067143031[/C][C]115.284314405635[/C][/ROW]
[ROW][C]0.83[/C][C]3902.66533412223[/C][C]119.581969231106[/C][/ROW]
[ROW][C]0.84[/C][C]3940.72712762581[/C][C]126.27675158538[/C][/ROW]
[ROW][C]0.85[/C][C]3981.60450478022[/C][C]133.021353498892[/C][/ROW]
[ROW][C]0.86[/C][C]4025.11788566334[/C][C]137.609892301398[/C][/ROW]
[ROW][C]0.87[/C][C]4070.64975427127[/C][C]138.722014147912[/C][/ROW]
[ROW][C]0.88[/C][C]4117.42088173899[/C][C]136.355145198103[/C][/ROW]
[ROW][C]0.89[/C][C]4164.80872097164[/C][C]131.682940077135[/C][/ROW]
[ROW][C]0.9[/C][C]4212.55346783858[/C][C]126.32459930823[/C][/ROW]
[ROW][C]0.91[/C][C]4260.74617365867[/C][C]121.391024797290[/C][/ROW]
[ROW][C]0.92[/C][C]4309.62091391532[/C][C]116.862595400492[/C][/ROW]
[ROW][C]0.93[/C][C]4359.29592600839[/C][C]111.834470597825[/C][/ROW]
[ROW][C]0.94[/C][C]4409.60291878406[/C][C]105.332831434325[/C][/ROW]
[ROW][C]0.95[/C][C]4459.99232115644[/C][C]96.7687312016468[/C][/ROW]
[ROW][C]0.96[/C][C]4509.52299738655[/C][C]85.3410174489278[/C][/ROW]
[ROW][C]0.97[/C][C]4557.60027098531[/C][C]70.527877110249[/C][/ROW]
[ROW][C]0.98[/C][C]4606.189111633[/C][C]57.1204092503026[/C][/ROW]
[ROW][C]0.99[/C][C]4657.88726383084[/C][C]59.5389245298498[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=38732&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=38732&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
0.011701.93265653004100.582434261679
0.021781.9743535877872.9101669870397
0.031839.6656118685756.8071684522096
0.041878.3766637357847.4756168636868
0.051906.4919149690542.1377677697821
0.061929.0360083630140.2483974254041
0.071948.9214897993241.6471277800749
0.081968.0248343930945.64360915163
0.091987.5336166792451.2227917849916
0.12008.1149923418457.579192040343
0.112030.0987465082464.4091968402876
0.122053.6586976082671.788886150084
0.132078.9310537920579.8647250570861
0.142106.0426333663488.5635230847175
0.152135.0703628716797.548714531636
0.162165.97632135944106.247422634124
0.172198.55695439528113.946284896731
0.182232.42910978321119.935180754252
0.192267.06217267112123.652638404518
0.22301.85404578057124.926122894040
0.212336.23471802647124.038949452975
0.222369.76752452502121.737357047554
0.232402.21399335506118.946922846192
0.242433.53946112043116.507946166065
0.252463.85965722726114.855076281518
0.262493.35149007588113.933086478070
0.272522.16267760546113.307715048729
0.282550.35030436246112.407756729121
0.292577.86233775718110.752381708623
0.32604.55791145626108.075450869571
0.312630.25008495120104.348803356909
0.322654.7522160951399.7297836058729
0.332677.9142217249394.4722693098363
0.342699.6432212883888.8553944950537
0.352719.9099731104183.1531205852498
0.362738.7459142440477.6128673228728
0.372756.235677680272.4477471313229
0.382772.5082182748667.8511039225062
0.392787.7277401359963.9718797750802
0.42802.0843841588160.9328213264314
0.412815.7842169763858.7920225476337
0.422829.0381528403257.5853409867148
0.432842.0497236165757.2476548311654
0.442855.0019695983857.6753395923632
0.452868.0441835619858.6765110975473
0.462881.2798154694160.0217538431182
0.472894.75741039561.431256495028
0.482908.4667476837962.6072732496425
0.492922.3420991594363.313135182173
0.52936.2735960847163.3483126543476
0.512950.1262110043162.6499082025699
0.522963.7642012500761.2632011042319
0.532977.0775469831459.3754235449126
0.542990.0064190700157.2660976195527
0.553002.5602582313255.3046929029391
0.563014.8295042487953.9042985231073
0.573026.9899019855353.4702401239847
0.583039.3009473706454.367086212576
0.593052.1007773438656.9282526783811
0.63065.7993029333861.4300083876444
0.613080.8697560946668.1045803599223
0.623097.8366828441477.0979011868192
0.633117.2567017181988.4793042677523
0.643139.68798651471102.133993332618
0.653165.64598463054117.731188424693
0.663195.54627854572134.674080638947
0.673229.63999824634152.088470328748
0.683267.95156740776168.872956208584
0.693310.23142653848183.781132618344
0.73355.93654460102195.591712018358
0.713404.24839296857203.239411264178
0.723454.13186143148206.021229503589
0.733504.43062773162203.711589528912
0.743553.98692144398196.604906678580
0.753601.76886017484185.528199590764
0.763646.98811240573171.697622284529
0.773689.19411080846156.618835960735
0.783728.33573736428141.910632547306
0.793764.78374583866129.183430934504
0.83799.30536760909119.905782839018
0.813832.97917466026115.158206019635
0.823867.04067143031115.284314405635
0.833902.66533412223119.581969231106
0.843940.72712762581126.27675158538
0.853981.60450478022133.021353498892
0.864025.11788566334137.609892301398
0.874070.64975427127138.722014147912
0.884117.42088173899136.355145198103
0.894164.80872097164131.682940077135
0.94212.55346783858126.32459930823
0.914260.74617365867121.391024797290
0.924309.62091391532116.862595400492
0.934359.29592600839111.834470597825
0.944409.60291878406105.332831434325
0.954459.9923211564496.7687312016468
0.964509.5229973865585.3410174489278
0.974557.6002709853170.527877110249
0.984606.18911163357.1204092503026
0.994657.8872638308459.5389245298498


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')