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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_harrell_davies.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationMon, 27 Oct 2008 16:10:40 -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/Oct/27/t122514547000eesnd3dwuqchw.htm/, Retrieved Sun, 19 May 2024 15:58:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19681, Retrieved Sun, 19 May 2024 15:58:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Harrell-Davis Quantiles] [Investigating dis...] [2007-10-22 20:06:26] [b9964c45117f7aac638ab9056d451faa]
-   PD  [Harrell-Davis Quantiles] [Q9] [2008-10-27 22:09:15] [6f54f97492451bf8edc5dd186465ee4a]
F           [Harrell-Davis Quantiles] [Q9 (0,1 step)] [2008-10-27 22:10:40] [3a23ee8a65a3056dd39b310a09ef5fc1] [Current]
Feedback Forum
2008-11-03 10:51:48 [Lindsay Heyndrickx] [reply] 
q10: Je kan dit het beste zien aan de autocorrelatie. Dit is inderdaad niet seizoensgebonden.
2008-11-03 16:55:23 [Lindsay Heyndrickx] [reply] 
q9: Hier werd te weinig uitleg bij gegeven.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1120400
1118600
1120100
1117300
1117700
1118300
1117000
1116900
1111900
1111800
1109500
1106400
1105100
1103600
1102500
1102100
1101800
1100200
1098100
1097300
1109900
1109700
1108100
1101400
1101400
1099900
1102000
1101500
1101200
1099500
1098200
1096500
1098300
1097500
1095400
1090300
1090300
1090400
1086600
1086400
1083000
1081400
1080300
1079200
1083800
1083700
1078700
1075500
1074000
1073000
1073000
1072000
1069000
1064000
1063000
1062000
1056000
1056000
1052000
1052000

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19681&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19681&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19681&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'George Udny Yule' @ 72.249.76.132






Harrell-Davis Quantiles
quantilesvaluestandard error
0.011052272.44586439870.447469945216
0.021052897.533047901936.18295401638
0.031053869.66095282824.09960024211
0.041055107.166764943469.55374069745
0.051056512.155971093956.82694143723
0.061058006.410591694346.27529137338
0.071059538.218102304649.06055106275
0.081061074.942878324866.14142685456
0.091062594.338218975006.23193628009
0.11064079.282188205076.21148237092
0.111065515.537198925076.28141870398
0.121066891.164594735005.81378109953
0.131068196.820713314869.64604795473
0.141069426.546243124685.27369407994
0.151070578.606016824481.06365030997
0.161071655.860255224285.23221330877
0.171072665.321001934126.87907439809
0.181073616.906575054016.41800361915
0.191074521.737821053952.68377427629
0.21075390.462897653926.69309847643
0.211076232.027526143923.42076073910
0.221077053.104024783928.20621059648
0.231077858.165129073933.31907158873
0.241078650.021625613934.46092805347
0.251079430.571171713933.01768847428
0.261080201.521115093937.01399130428
0.271080964.918453723949.91618398735
0.281081723.408627843979.92334727362
0.291082480.223378414029.42343398281
0.31083238.951467424100.97912028388
0.311084003.171753304193.51624978273
0.321084776.030973354302.15010852939
0.331085559.836932844419.40214949469
0.341086355.719747674537.2535452544
0.351087163.395288414646.81647825363
0.361087981.049262954736.5745861329
0.371088805.348323914798.68975647088
0.381089631.575491474827.14808022008
0.391090453.879658714813.32245226148
0.41091265.621716544754.92141344322
0.411092059.792291794647.98949911187
0.421092829.468569224496.96571674384
0.431093568.271379984304.22610835901
0.441094270.780410834078.47057462229
0.451094932.866690923826.48747263512
0.461095551.908444433561.27101046803
0.471096126.868832093291.38105698154
0.481096658.230634233027.72790591007
0.491097147.801075492777.75029074039
0.51097598.416729242549.82525173635
0.511098013.590878172347.2025995424
0.521098397.151738782170.28508071632
0.531098752.918700772017.75938728216
0.541099084.455665621885.18596784837
0.551099394.92733781771.73619788618
0.561099687.068317001670.59077287677
0.571099963.258652391580.83409751124
0.581100225.685443791499.80797019661
0.591100476.559738281428.08867703778
0.61100718.35218281368.49460681127
0.611100954.009689281324.95898116703
0.621101187.118216751301.258951725
0.631101421.982864161305.03931496760
0.641101663.604986651339.88453529437
0.651101917.546376181410.41915481071
0.661102189.682299211515.98309553158
0.671102485.858099111656.55775005738
0.681102811.477760301824.45729432603
0.691103171.066469572013.22172512573
0.71103567.861252222213.08103823045
0.711104003.491825642413.34113139800
0.721104477.814818262602.47279235248
0.731104988.955148682769.76845706397
0.741105533.585975922906.83345318383
0.751106107.442310013009.97414833586
0.761106706.015257593077.68906789659
0.771107325.320283163113.95796917161
0.781107962.584806473129.60201044068
0.791108616.672984413135.16510772761
0.81109288.075293903144.63519304053
0.811109978.351140563166.71353032483
0.821110689.028124613203.96551088614
0.831111420.119032723247.53828503649
0.841112168.583062523279.27273469127
0.851112927.178137173274.67933298186
0.861113684.166996963209.7054718041
0.871114424.208672933065.42330912087
0.881115130.490945382837.52235753245
0.891115787.80116992536.48151451505
0.91116385.902703692188.86857165920
0.911116922.388674501833.0413002447
0.921117404.157928751511.57654870949
0.931117846.735382981262.93240965560
0.941118270.771353231111.02256578524
0.951118695.336875161050.74824502069
0.961119128.550375831031.70502381407
0.971119558.10818786968.383346924947
0.981119947.10931611788.433942446393
0.991120242.34587836509.749860889715

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 1052272.44586439 & 870.447469945216 \tabularnewline
0.02 & 1052897.53304790 & 1936.18295401638 \tabularnewline
0.03 & 1053869.6609528 & 2824.09960024211 \tabularnewline
0.04 & 1055107.16676494 & 3469.55374069745 \tabularnewline
0.05 & 1056512.15597109 & 3956.82694143723 \tabularnewline
0.06 & 1058006.41059169 & 4346.27529137338 \tabularnewline
0.07 & 1059538.21810230 & 4649.06055106275 \tabularnewline
0.08 & 1061074.94287832 & 4866.14142685456 \tabularnewline
0.09 & 1062594.33821897 & 5006.23193628009 \tabularnewline
0.1 & 1064079.28218820 & 5076.21148237092 \tabularnewline
0.11 & 1065515.53719892 & 5076.28141870398 \tabularnewline
0.12 & 1066891.16459473 & 5005.81378109953 \tabularnewline
0.13 & 1068196.82071331 & 4869.64604795473 \tabularnewline
0.14 & 1069426.54624312 & 4685.27369407994 \tabularnewline
0.15 & 1070578.60601682 & 4481.06365030997 \tabularnewline
0.16 & 1071655.86025522 & 4285.23221330877 \tabularnewline
0.17 & 1072665.32100193 & 4126.87907439809 \tabularnewline
0.18 & 1073616.90657505 & 4016.41800361915 \tabularnewline
0.19 & 1074521.73782105 & 3952.68377427629 \tabularnewline
0.2 & 1075390.46289765 & 3926.69309847643 \tabularnewline
0.21 & 1076232.02752614 & 3923.42076073910 \tabularnewline
0.22 & 1077053.10402478 & 3928.20621059648 \tabularnewline
0.23 & 1077858.16512907 & 3933.31907158873 \tabularnewline
0.24 & 1078650.02162561 & 3934.46092805347 \tabularnewline
0.25 & 1079430.57117171 & 3933.01768847428 \tabularnewline
0.26 & 1080201.52111509 & 3937.01399130428 \tabularnewline
0.27 & 1080964.91845372 & 3949.91618398735 \tabularnewline
0.28 & 1081723.40862784 & 3979.92334727362 \tabularnewline
0.29 & 1082480.22337841 & 4029.42343398281 \tabularnewline
0.3 & 1083238.95146742 & 4100.97912028388 \tabularnewline
0.31 & 1084003.17175330 & 4193.51624978273 \tabularnewline
0.32 & 1084776.03097335 & 4302.15010852939 \tabularnewline
0.33 & 1085559.83693284 & 4419.40214949469 \tabularnewline
0.34 & 1086355.71974767 & 4537.2535452544 \tabularnewline
0.35 & 1087163.39528841 & 4646.81647825363 \tabularnewline
0.36 & 1087981.04926295 & 4736.5745861329 \tabularnewline
0.37 & 1088805.34832391 & 4798.68975647088 \tabularnewline
0.38 & 1089631.57549147 & 4827.14808022008 \tabularnewline
0.39 & 1090453.87965871 & 4813.32245226148 \tabularnewline
0.4 & 1091265.62171654 & 4754.92141344322 \tabularnewline
0.41 & 1092059.79229179 & 4647.98949911187 \tabularnewline
0.42 & 1092829.46856922 & 4496.96571674384 \tabularnewline
0.43 & 1093568.27137998 & 4304.22610835901 \tabularnewline
0.44 & 1094270.78041083 & 4078.47057462229 \tabularnewline
0.45 & 1094932.86669092 & 3826.48747263512 \tabularnewline
0.46 & 1095551.90844443 & 3561.27101046803 \tabularnewline
0.47 & 1096126.86883209 & 3291.38105698154 \tabularnewline
0.48 & 1096658.23063423 & 3027.72790591007 \tabularnewline
0.49 & 1097147.80107549 & 2777.75029074039 \tabularnewline
0.5 & 1097598.41672924 & 2549.82525173635 \tabularnewline
0.51 & 1098013.59087817 & 2347.2025995424 \tabularnewline
0.52 & 1098397.15173878 & 2170.28508071632 \tabularnewline
0.53 & 1098752.91870077 & 2017.75938728216 \tabularnewline
0.54 & 1099084.45566562 & 1885.18596784837 \tabularnewline
0.55 & 1099394.9273378 & 1771.73619788618 \tabularnewline
0.56 & 1099687.06831700 & 1670.59077287677 \tabularnewline
0.57 & 1099963.25865239 & 1580.83409751124 \tabularnewline
0.58 & 1100225.68544379 & 1499.80797019661 \tabularnewline
0.59 & 1100476.55973828 & 1428.08867703778 \tabularnewline
0.6 & 1100718.3521828 & 1368.49460681127 \tabularnewline
0.61 & 1100954.00968928 & 1324.95898116703 \tabularnewline
0.62 & 1101187.11821675 & 1301.258951725 \tabularnewline
0.63 & 1101421.98286416 & 1305.03931496760 \tabularnewline
0.64 & 1101663.60498665 & 1339.88453529437 \tabularnewline
0.65 & 1101917.54637618 & 1410.41915481071 \tabularnewline
0.66 & 1102189.68229921 & 1515.98309553158 \tabularnewline
0.67 & 1102485.85809911 & 1656.55775005738 \tabularnewline
0.68 & 1102811.47776030 & 1824.45729432603 \tabularnewline
0.69 & 1103171.06646957 & 2013.22172512573 \tabularnewline
0.7 & 1103567.86125222 & 2213.08103823045 \tabularnewline
0.71 & 1104003.49182564 & 2413.34113139800 \tabularnewline
0.72 & 1104477.81481826 & 2602.47279235248 \tabularnewline
0.73 & 1104988.95514868 & 2769.76845706397 \tabularnewline
0.74 & 1105533.58597592 & 2906.83345318383 \tabularnewline
0.75 & 1106107.44231001 & 3009.97414833586 \tabularnewline
0.76 & 1106706.01525759 & 3077.68906789659 \tabularnewline
0.77 & 1107325.32028316 & 3113.95796917161 \tabularnewline
0.78 & 1107962.58480647 & 3129.60201044068 \tabularnewline
0.79 & 1108616.67298441 & 3135.16510772761 \tabularnewline
0.8 & 1109288.07529390 & 3144.63519304053 \tabularnewline
0.81 & 1109978.35114056 & 3166.71353032483 \tabularnewline
0.82 & 1110689.02812461 & 3203.96551088614 \tabularnewline
0.83 & 1111420.11903272 & 3247.53828503649 \tabularnewline
0.84 & 1112168.58306252 & 3279.27273469127 \tabularnewline
0.85 & 1112927.17813717 & 3274.67933298186 \tabularnewline
0.86 & 1113684.16699696 & 3209.7054718041 \tabularnewline
0.87 & 1114424.20867293 & 3065.42330912087 \tabularnewline
0.88 & 1115130.49094538 & 2837.52235753245 \tabularnewline
0.89 & 1115787.8011699 & 2536.48151451505 \tabularnewline
0.9 & 1116385.90270369 & 2188.86857165920 \tabularnewline
0.91 & 1116922.38867450 & 1833.0413002447 \tabularnewline
0.92 & 1117404.15792875 & 1511.57654870949 \tabularnewline
0.93 & 1117846.73538298 & 1262.93240965560 \tabularnewline
0.94 & 1118270.77135323 & 1111.02256578524 \tabularnewline
0.95 & 1118695.33687516 & 1050.74824502069 \tabularnewline
0.96 & 1119128.55037583 & 1031.70502381407 \tabularnewline
0.97 & 1119558.10818786 & 968.383346924947 \tabularnewline
0.98 & 1119947.10931611 & 788.433942446393 \tabularnewline
0.99 & 1120242.34587836 & 509.749860889715 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19681&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]1052272.44586439[/C][C]870.447469945216[/C][/ROW]
[ROW][C]0.02[/C][C]1052897.53304790[/C][C]1936.18295401638[/C][/ROW]
[ROW][C]0.03[/C][C]1053869.6609528[/C][C]2824.09960024211[/C][/ROW]
[ROW][C]0.04[/C][C]1055107.16676494[/C][C]3469.55374069745[/C][/ROW]
[ROW][C]0.05[/C][C]1056512.15597109[/C][C]3956.82694143723[/C][/ROW]
[ROW][C]0.06[/C][C]1058006.41059169[/C][C]4346.27529137338[/C][/ROW]
[ROW][C]0.07[/C][C]1059538.21810230[/C][C]4649.06055106275[/C][/ROW]
[ROW][C]0.08[/C][C]1061074.94287832[/C][C]4866.14142685456[/C][/ROW]
[ROW][C]0.09[/C][C]1062594.33821897[/C][C]5006.23193628009[/C][/ROW]
[ROW][C]0.1[/C][C]1064079.28218820[/C][C]5076.21148237092[/C][/ROW]
[ROW][C]0.11[/C][C]1065515.53719892[/C][C]5076.28141870398[/C][/ROW]
[ROW][C]0.12[/C][C]1066891.16459473[/C][C]5005.81378109953[/C][/ROW]
[ROW][C]0.13[/C][C]1068196.82071331[/C][C]4869.64604795473[/C][/ROW]
[ROW][C]0.14[/C][C]1069426.54624312[/C][C]4685.27369407994[/C][/ROW]
[ROW][C]0.15[/C][C]1070578.60601682[/C][C]4481.06365030997[/C][/ROW]
[ROW][C]0.16[/C][C]1071655.86025522[/C][C]4285.23221330877[/C][/ROW]
[ROW][C]0.17[/C][C]1072665.32100193[/C][C]4126.87907439809[/C][/ROW]
[ROW][C]0.18[/C][C]1073616.90657505[/C][C]4016.41800361915[/C][/ROW]
[ROW][C]0.19[/C][C]1074521.73782105[/C][C]3952.68377427629[/C][/ROW]
[ROW][C]0.2[/C][C]1075390.46289765[/C][C]3926.69309847643[/C][/ROW]
[ROW][C]0.21[/C][C]1076232.02752614[/C][C]3923.42076073910[/C][/ROW]
[ROW][C]0.22[/C][C]1077053.10402478[/C][C]3928.20621059648[/C][/ROW]
[ROW][C]0.23[/C][C]1077858.16512907[/C][C]3933.31907158873[/C][/ROW]
[ROW][C]0.24[/C][C]1078650.02162561[/C][C]3934.46092805347[/C][/ROW]
[ROW][C]0.25[/C][C]1079430.57117171[/C][C]3933.01768847428[/C][/ROW]
[ROW][C]0.26[/C][C]1080201.52111509[/C][C]3937.01399130428[/C][/ROW]
[ROW][C]0.27[/C][C]1080964.91845372[/C][C]3949.91618398735[/C][/ROW]
[ROW][C]0.28[/C][C]1081723.40862784[/C][C]3979.92334727362[/C][/ROW]
[ROW][C]0.29[/C][C]1082480.22337841[/C][C]4029.42343398281[/C][/ROW]
[ROW][C]0.3[/C][C]1083238.95146742[/C][C]4100.97912028388[/C][/ROW]
[ROW][C]0.31[/C][C]1084003.17175330[/C][C]4193.51624978273[/C][/ROW]
[ROW][C]0.32[/C][C]1084776.03097335[/C][C]4302.15010852939[/C][/ROW]
[ROW][C]0.33[/C][C]1085559.83693284[/C][C]4419.40214949469[/C][/ROW]
[ROW][C]0.34[/C][C]1086355.71974767[/C][C]4537.2535452544[/C][/ROW]
[ROW][C]0.35[/C][C]1087163.39528841[/C][C]4646.81647825363[/C][/ROW]
[ROW][C]0.36[/C][C]1087981.04926295[/C][C]4736.5745861329[/C][/ROW]
[ROW][C]0.37[/C][C]1088805.34832391[/C][C]4798.68975647088[/C][/ROW]
[ROW][C]0.38[/C][C]1089631.57549147[/C][C]4827.14808022008[/C][/ROW]
[ROW][C]0.39[/C][C]1090453.87965871[/C][C]4813.32245226148[/C][/ROW]
[ROW][C]0.4[/C][C]1091265.62171654[/C][C]4754.92141344322[/C][/ROW]
[ROW][C]0.41[/C][C]1092059.79229179[/C][C]4647.98949911187[/C][/ROW]
[ROW][C]0.42[/C][C]1092829.46856922[/C][C]4496.96571674384[/C][/ROW]
[ROW][C]0.43[/C][C]1093568.27137998[/C][C]4304.22610835901[/C][/ROW]
[ROW][C]0.44[/C][C]1094270.78041083[/C][C]4078.47057462229[/C][/ROW]
[ROW][C]0.45[/C][C]1094932.86669092[/C][C]3826.48747263512[/C][/ROW]
[ROW][C]0.46[/C][C]1095551.90844443[/C][C]3561.27101046803[/C][/ROW]
[ROW][C]0.47[/C][C]1096126.86883209[/C][C]3291.38105698154[/C][/ROW]
[ROW][C]0.48[/C][C]1096658.23063423[/C][C]3027.72790591007[/C][/ROW]
[ROW][C]0.49[/C][C]1097147.80107549[/C][C]2777.75029074039[/C][/ROW]
[ROW][C]0.5[/C][C]1097598.41672924[/C][C]2549.82525173635[/C][/ROW]
[ROW][C]0.51[/C][C]1098013.59087817[/C][C]2347.2025995424[/C][/ROW]
[ROW][C]0.52[/C][C]1098397.15173878[/C][C]2170.28508071632[/C][/ROW]
[ROW][C]0.53[/C][C]1098752.91870077[/C][C]2017.75938728216[/C][/ROW]
[ROW][C]0.54[/C][C]1099084.45566562[/C][C]1885.18596784837[/C][/ROW]
[ROW][C]0.55[/C][C]1099394.9273378[/C][C]1771.73619788618[/C][/ROW]
[ROW][C]0.56[/C][C]1099687.06831700[/C][C]1670.59077287677[/C][/ROW]
[ROW][C]0.57[/C][C]1099963.25865239[/C][C]1580.83409751124[/C][/ROW]
[ROW][C]0.58[/C][C]1100225.68544379[/C][C]1499.80797019661[/C][/ROW]
[ROW][C]0.59[/C][C]1100476.55973828[/C][C]1428.08867703778[/C][/ROW]
[ROW][C]0.6[/C][C]1100718.3521828[/C][C]1368.49460681127[/C][/ROW]
[ROW][C]0.61[/C][C]1100954.00968928[/C][C]1324.95898116703[/C][/ROW]
[ROW][C]0.62[/C][C]1101187.11821675[/C][C]1301.258951725[/C][/ROW]
[ROW][C]0.63[/C][C]1101421.98286416[/C][C]1305.03931496760[/C][/ROW]
[ROW][C]0.64[/C][C]1101663.60498665[/C][C]1339.88453529437[/C][/ROW]
[ROW][C]0.65[/C][C]1101917.54637618[/C][C]1410.41915481071[/C][/ROW]
[ROW][C]0.66[/C][C]1102189.68229921[/C][C]1515.98309553158[/C][/ROW]
[ROW][C]0.67[/C][C]1102485.85809911[/C][C]1656.55775005738[/C][/ROW]
[ROW][C]0.68[/C][C]1102811.47776030[/C][C]1824.45729432603[/C][/ROW]
[ROW][C]0.69[/C][C]1103171.06646957[/C][C]2013.22172512573[/C][/ROW]
[ROW][C]0.7[/C][C]1103567.86125222[/C][C]2213.08103823045[/C][/ROW]
[ROW][C]0.71[/C][C]1104003.49182564[/C][C]2413.34113139800[/C][/ROW]
[ROW][C]0.72[/C][C]1104477.81481826[/C][C]2602.47279235248[/C][/ROW]
[ROW][C]0.73[/C][C]1104988.95514868[/C][C]2769.76845706397[/C][/ROW]
[ROW][C]0.74[/C][C]1105533.58597592[/C][C]2906.83345318383[/C][/ROW]
[ROW][C]0.75[/C][C]1106107.44231001[/C][C]3009.97414833586[/C][/ROW]
[ROW][C]0.76[/C][C]1106706.01525759[/C][C]3077.68906789659[/C][/ROW]
[ROW][C]0.77[/C][C]1107325.32028316[/C][C]3113.95796917161[/C][/ROW]
[ROW][C]0.78[/C][C]1107962.58480647[/C][C]3129.60201044068[/C][/ROW]
[ROW][C]0.79[/C][C]1108616.67298441[/C][C]3135.16510772761[/C][/ROW]
[ROW][C]0.8[/C][C]1109288.07529390[/C][C]3144.63519304053[/C][/ROW]
[ROW][C]0.81[/C][C]1109978.35114056[/C][C]3166.71353032483[/C][/ROW]
[ROW][C]0.82[/C][C]1110689.02812461[/C][C]3203.96551088614[/C][/ROW]
[ROW][C]0.83[/C][C]1111420.11903272[/C][C]3247.53828503649[/C][/ROW]
[ROW][C]0.84[/C][C]1112168.58306252[/C][C]3279.27273469127[/C][/ROW]
[ROW][C]0.85[/C][C]1112927.17813717[/C][C]3274.67933298186[/C][/ROW]
[ROW][C]0.86[/C][C]1113684.16699696[/C][C]3209.7054718041[/C][/ROW]
[ROW][C]0.87[/C][C]1114424.20867293[/C][C]3065.42330912087[/C][/ROW]
[ROW][C]0.88[/C][C]1115130.49094538[/C][C]2837.52235753245[/C][/ROW]
[ROW][C]0.89[/C][C]1115787.8011699[/C][C]2536.48151451505[/C][/ROW]
[ROW][C]0.9[/C][C]1116385.90270369[/C][C]2188.86857165920[/C][/ROW]
[ROW][C]0.91[/C][C]1116922.38867450[/C][C]1833.0413002447[/C][/ROW]
[ROW][C]0.92[/C][C]1117404.15792875[/C][C]1511.57654870949[/C][/ROW]
[ROW][C]0.93[/C][C]1117846.73538298[/C][C]1262.93240965560[/C][/ROW]
[ROW][C]0.94[/C][C]1118270.77135323[/C][C]1111.02256578524[/C][/ROW]
[ROW][C]0.95[/C][C]1118695.33687516[/C][C]1050.74824502069[/C][/ROW]
[ROW][C]0.96[/C][C]1119128.55037583[/C][C]1031.70502381407[/C][/ROW]
[ROW][C]0.97[/C][C]1119558.10818786[/C][C]968.383346924947[/C][/ROW]
[ROW][C]0.98[/C][C]1119947.10931611[/C][C]788.433942446393[/C][/ROW]
[ROW][C]0.99[/C][C]1120242.34587836[/C][C]509.749860889715[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19681&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19681&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
0.011052272.44586439870.447469945216
0.021052897.533047901936.18295401638
0.031053869.66095282824.09960024211
0.041055107.166764943469.55374069745
0.051056512.155971093956.82694143723
0.061058006.410591694346.27529137338
0.071059538.218102304649.06055106275
0.081061074.942878324866.14142685456
0.091062594.338218975006.23193628009
0.11064079.282188205076.21148237092
0.111065515.537198925076.28141870398
0.121066891.164594735005.81378109953
0.131068196.820713314869.64604795473
0.141069426.546243124685.27369407994
0.151070578.606016824481.06365030997
0.161071655.860255224285.23221330877
0.171072665.321001934126.87907439809
0.181073616.906575054016.41800361915
0.191074521.737821053952.68377427629
0.21075390.462897653926.69309847643
0.211076232.027526143923.42076073910
0.221077053.104024783928.20621059648
0.231077858.165129073933.31907158873
0.241078650.021625613934.46092805347
0.251079430.571171713933.01768847428
0.261080201.521115093937.01399130428
0.271080964.918453723949.91618398735
0.281081723.408627843979.92334727362
0.291082480.223378414029.42343398281
0.31083238.951467424100.97912028388
0.311084003.171753304193.51624978273
0.321084776.030973354302.15010852939
0.331085559.836932844419.40214949469
0.341086355.719747674537.2535452544
0.351087163.395288414646.81647825363
0.361087981.049262954736.5745861329
0.371088805.348323914798.68975647088
0.381089631.575491474827.14808022008
0.391090453.879658714813.32245226148
0.41091265.621716544754.92141344322
0.411092059.792291794647.98949911187
0.421092829.468569224496.96571674384
0.431093568.271379984304.22610835901
0.441094270.780410834078.47057462229
0.451094932.866690923826.48747263512
0.461095551.908444433561.27101046803
0.471096126.868832093291.38105698154
0.481096658.230634233027.72790591007
0.491097147.801075492777.75029074039
0.51097598.416729242549.82525173635
0.511098013.590878172347.2025995424
0.521098397.151738782170.28508071632
0.531098752.918700772017.75938728216
0.541099084.455665621885.18596784837
0.551099394.92733781771.73619788618
0.561099687.068317001670.59077287677
0.571099963.258652391580.83409751124
0.581100225.685443791499.80797019661
0.591100476.559738281428.08867703778
0.61100718.35218281368.49460681127
0.611100954.009689281324.95898116703
0.621101187.118216751301.258951725
0.631101421.982864161305.03931496760
0.641101663.604986651339.88453529437
0.651101917.546376181410.41915481071
0.661102189.682299211515.98309553158
0.671102485.858099111656.55775005738
0.681102811.477760301824.45729432603
0.691103171.066469572013.22172512573
0.71103567.861252222213.08103823045
0.711104003.491825642413.34113139800
0.721104477.814818262602.47279235248
0.731104988.955148682769.76845706397
0.741105533.585975922906.83345318383
0.751106107.442310013009.97414833586
0.761106706.015257593077.68906789659
0.771107325.320283163113.95796917161
0.781107962.584806473129.60201044068
0.791108616.672984413135.16510772761
0.81109288.075293903144.63519304053
0.811109978.351140563166.71353032483
0.821110689.028124613203.96551088614
0.831111420.119032723247.53828503649
0.841112168.583062523279.27273469127
0.851112927.178137173274.67933298186
0.861113684.166996963209.7054718041
0.871114424.208672933065.42330912087
0.881115130.490945382837.52235753245
0.891115787.80116992536.48151451505
0.91116385.902703692188.86857165920
0.911116922.388674501833.0413002447
0.921117404.157928751511.57654870949
0.931117846.735382981262.93240965560
0.941118270.771353231111.02256578524
0.951118695.336875161050.74824502069
0.961119128.550375831031.70502381407
0.971119558.10818786968.383346924947
0.981119947.10931611788.433942446393
0.991120242.34587836509.749860889715


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 0 ;
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')