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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, 03 Aug 2012 08:54:04 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Aug/03/t1343998483y4pjcoyzu7nvcxj.htm/, Retrieved Mon, 29 Apr 2024 19:39:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168994, Retrieved Mon, 29 Apr 2024 19:39:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSelleslaghs Tessa
Estimated Impact112

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] [Tijdreeks B stap 7] [2012-08-03 12:54:04] [5f178b5bce8a01d64692a8a5c649399b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1020
970
1030
970
1070
1650
1010
980
1050
1010
1040
1120
1090
1060
990
950
1540
870
1070
1050
1020
960
1100
1190
1040
1090
1050
850
1100
850
1040
990
1040
1100
1030
1290
1040
1170
1040
860
1090
870
1080
1000
980
1080
1040
1280
1140
1220
1080
790
1020
830
1150
1030
900
1140
1010
1270
1090
1090
980
850
1010
810
1070
1040
880
1110
1010
1230
490
1040
1010
860
1010
800
1130
1040
940
1070
1030
1320
1040
1070
1070
770
1010
810
1150
1030
890
1010
1120
1250
990
1020
1110
830
1030
870
1260
980
940
970
1100
1320

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 seconds
R Server'AstonUniversity' @ aston.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 & 12 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168994&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]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168994&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168994&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 time12 seconds
R Server'AstonUniversity' @ aston.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01607.27084595484172.490434202153
0.02722.08938067963872.5168981811601
0.03778.89945295890428.9974305092851
0.04802.18224121312818.6070870984396
0.05814.4925810220117.774550855695
0.06823.96797924792518.1288080368466
0.07832.46525680561717.8768647626016
0.08840.21007885171317.0345590192739
0.09847.23087348059416.2209218159045
0.1853.70005075614516.1194284465699
0.11859.94742919331517.1838872421612
0.12866.37617934484619.529212551665
0.13873.36539525456222.9513984008511
0.14881.18737512435526.9806599358685
0.15889.94859258053930.9641334013338
0.16899.5634630851934.2153666620801
0.17909.76981599320336.1725445451004
0.18920.18529274860736.5440208525292
0.19930.38944633334235.3596660922524
0.2940.00711269000432.9250642213131
0.21948.77021427614729.7183972284907
0.22956.5455220978926.2532605510166
0.23963.3286439634922.9709744123399
0.24969.21379944696620.1773306566489
0.25974.35242033452518.0159272106893
0.26978.91223813593216.4803299442005
0.27983.04473526679515.445837176266
0.28986.86479530040814.7251936789386
0.29990.44315911134414.1249868308874
0.3993.810028930213.4931046657531
0.31996.9666553699212.7449043137136
0.32999.90086930614711.8702995717285
0.331002.6023458235810.9222197410981
0.341005.074015440889.9951938863497
0.351007.337407443839.19745778489885
0.361009.431504054328.61618555421447
0.371011.406406286528.29371222060731
0.381013.31427739778.21377217440993
0.391015.200353718548.31434068349928
0.41017.09630850238.50765609285664
0.411019.017200235328.70695613420358
0.421020.962045439038.84396525638545
0.431022.917115081828.87597894108624
0.441024.860601307878.7835217814038
0.451026.767373303648.5686895965718
0.461028.612994672718.24501121262753
0.471030.376763717247.83673716526423
0.481032.044011085227.36994335352387
0.491033.608076064856.88546377079392
0.51035.072245216346.42337346142476
0.511036.451570865526.04362469616184
0.521037.774077147745.81560808641492
0.531039.080607943375.80744654863236
0.541040.422614784156.07685304772034
0.551041.857555368956.64125044246194
0.561043.442188077087.47085215073933
0.571045.224728004748.49617978965435
0.581047.237360843329.61100672334284
0.591049.4907999954210.7044623142532
0.61051.9723060581611.6628087284756
0.611054.6478750242612.3964126953906
0.621057.4682937872112.854445952941
0.631060.3777348299913.0332966374698
0.641063.3228486129212.9694960492753
0.651066.2601883641712.7293667532005
0.661069.160366048912.3946381571333
0.671072.0084363383612.0331876333707
0.681074.8012567792311.6900751753241
0.691077.5435072313911.3862680473273
0.71080.2443113723111.1227961988649
0.711082.9159074330610.8995379439927
0.721085.5748031863210.7308386663084
0.731088.244762601910.6487368216786
0.741090.9602375754810.7031838027651
0.751093.7687063352610.9510423216677
0.761096.7307852075511.4375864174683
0.771099.917762151912.1909128263164
0.781103.4071799810213.2094812835773
0.791107.2781614674514.4647853441442
0.81111.6091516099615.9167384037203
0.811116.4811942837117.5398670520939
0.821121.9888815332319.355190814602
0.831128.2577285723721.4608747497218
0.841135.4607897788624.0212282072464
0.851143.8208135408227.1961929085264
0.861153.5817994064531.0040695174972
0.871164.9412039793635.1656862451874
0.881177.9536784458839.0578036212469
0.891192.4432743170741.8407362216007
0.91207.9787811246542.7484234352695
0.911223.9605517773141.4458441954605
0.921239.8360722532938.3059939771707
0.931255.4411069051934.4828126083624
0.941271.5454475472131.9371057894419
0.951290.9459609053334.1329325452537
0.961320.4916840484148.3521189664954
0.971372.5712238997382.722501499754
0.981459.416676333125.378624573518
0.991571.03999646515132.992013217137

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 607.27084595484 & 172.490434202153 \tabularnewline
0.02 & 722.089380679638 & 72.5168981811601 \tabularnewline
0.03 & 778.899452958904 & 28.9974305092851 \tabularnewline
0.04 & 802.182241213128 & 18.6070870984396 \tabularnewline
0.05 & 814.49258102201 & 17.774550855695 \tabularnewline
0.06 & 823.967979247925 & 18.1288080368466 \tabularnewline
0.07 & 832.465256805617 & 17.8768647626016 \tabularnewline
0.08 & 840.210078851713 & 17.0345590192739 \tabularnewline
0.09 & 847.230873480594 & 16.2209218159045 \tabularnewline
0.1 & 853.700050756145 & 16.1194284465699 \tabularnewline
0.11 & 859.947429193315 & 17.1838872421612 \tabularnewline
0.12 & 866.376179344846 & 19.529212551665 \tabularnewline
0.13 & 873.365395254562 & 22.9513984008511 \tabularnewline
0.14 & 881.187375124355 & 26.9806599358685 \tabularnewline
0.15 & 889.948592580539 & 30.9641334013338 \tabularnewline
0.16 & 899.56346308519 & 34.2153666620801 \tabularnewline
0.17 & 909.769815993203 & 36.1725445451004 \tabularnewline
0.18 & 920.185292748607 & 36.5440208525292 \tabularnewline
0.19 & 930.389446333342 & 35.3596660922524 \tabularnewline
0.2 & 940.007112690004 & 32.9250642213131 \tabularnewline
0.21 & 948.770214276147 & 29.7183972284907 \tabularnewline
0.22 & 956.54552209789 & 26.2532605510166 \tabularnewline
0.23 & 963.32864396349 & 22.9709744123399 \tabularnewline
0.24 & 969.213799446966 & 20.1773306566489 \tabularnewline
0.25 & 974.352420334525 & 18.0159272106893 \tabularnewline
0.26 & 978.912238135932 & 16.4803299442005 \tabularnewline
0.27 & 983.044735266795 & 15.445837176266 \tabularnewline
0.28 & 986.864795300408 & 14.7251936789386 \tabularnewline
0.29 & 990.443159111344 & 14.1249868308874 \tabularnewline
0.3 & 993.8100289302 & 13.4931046657531 \tabularnewline
0.31 & 996.96665536992 & 12.7449043137136 \tabularnewline
0.32 & 999.900869306147 & 11.8702995717285 \tabularnewline
0.33 & 1002.60234582358 & 10.9222197410981 \tabularnewline
0.34 & 1005.07401544088 & 9.9951938863497 \tabularnewline
0.35 & 1007.33740744383 & 9.19745778489885 \tabularnewline
0.36 & 1009.43150405432 & 8.61618555421447 \tabularnewline
0.37 & 1011.40640628652 & 8.29371222060731 \tabularnewline
0.38 & 1013.3142773977 & 8.21377217440993 \tabularnewline
0.39 & 1015.20035371854 & 8.31434068349928 \tabularnewline
0.4 & 1017.0963085023 & 8.50765609285664 \tabularnewline
0.41 & 1019.01720023532 & 8.70695613420358 \tabularnewline
0.42 & 1020.96204543903 & 8.84396525638545 \tabularnewline
0.43 & 1022.91711508182 & 8.87597894108624 \tabularnewline
0.44 & 1024.86060130787 & 8.7835217814038 \tabularnewline
0.45 & 1026.76737330364 & 8.5686895965718 \tabularnewline
0.46 & 1028.61299467271 & 8.24501121262753 \tabularnewline
0.47 & 1030.37676371724 & 7.83673716526423 \tabularnewline
0.48 & 1032.04401108522 & 7.36994335352387 \tabularnewline
0.49 & 1033.60807606485 & 6.88546377079392 \tabularnewline
0.5 & 1035.07224521634 & 6.42337346142476 \tabularnewline
0.51 & 1036.45157086552 & 6.04362469616184 \tabularnewline
0.52 & 1037.77407714774 & 5.81560808641492 \tabularnewline
0.53 & 1039.08060794337 & 5.80744654863236 \tabularnewline
0.54 & 1040.42261478415 & 6.07685304772034 \tabularnewline
0.55 & 1041.85755536895 & 6.64125044246194 \tabularnewline
0.56 & 1043.44218807708 & 7.47085215073933 \tabularnewline
0.57 & 1045.22472800474 & 8.49617978965435 \tabularnewline
0.58 & 1047.23736084332 & 9.61100672334284 \tabularnewline
0.59 & 1049.49079999542 & 10.7044623142532 \tabularnewline
0.6 & 1051.97230605816 & 11.6628087284756 \tabularnewline
0.61 & 1054.64787502426 & 12.3964126953906 \tabularnewline
0.62 & 1057.46829378721 & 12.854445952941 \tabularnewline
0.63 & 1060.37773482999 & 13.0332966374698 \tabularnewline
0.64 & 1063.32284861292 & 12.9694960492753 \tabularnewline
0.65 & 1066.26018836417 & 12.7293667532005 \tabularnewline
0.66 & 1069.1603660489 & 12.3946381571333 \tabularnewline
0.67 & 1072.00843633836 & 12.0331876333707 \tabularnewline
0.68 & 1074.80125677923 & 11.6900751753241 \tabularnewline
0.69 & 1077.54350723139 & 11.3862680473273 \tabularnewline
0.7 & 1080.24431137231 & 11.1227961988649 \tabularnewline
0.71 & 1082.91590743306 & 10.8995379439927 \tabularnewline
0.72 & 1085.57480318632 & 10.7308386663084 \tabularnewline
0.73 & 1088.2447626019 & 10.6487368216786 \tabularnewline
0.74 & 1090.96023757548 & 10.7031838027651 \tabularnewline
0.75 & 1093.76870633526 & 10.9510423216677 \tabularnewline
0.76 & 1096.73078520755 & 11.4375864174683 \tabularnewline
0.77 & 1099.9177621519 & 12.1909128263164 \tabularnewline
0.78 & 1103.40717998102 & 13.2094812835773 \tabularnewline
0.79 & 1107.27816146745 & 14.4647853441442 \tabularnewline
0.8 & 1111.60915160996 & 15.9167384037203 \tabularnewline
0.81 & 1116.48119428371 & 17.5398670520939 \tabularnewline
0.82 & 1121.98888153323 & 19.355190814602 \tabularnewline
0.83 & 1128.25772857237 & 21.4608747497218 \tabularnewline
0.84 & 1135.46078977886 & 24.0212282072464 \tabularnewline
0.85 & 1143.82081354082 & 27.1961929085264 \tabularnewline
0.86 & 1153.58179940645 & 31.0040695174972 \tabularnewline
0.87 & 1164.94120397936 & 35.1656862451874 \tabularnewline
0.88 & 1177.95367844588 & 39.0578036212469 \tabularnewline
0.89 & 1192.44327431707 & 41.8407362216007 \tabularnewline
0.9 & 1207.97878112465 & 42.7484234352695 \tabularnewline
0.91 & 1223.96055177731 & 41.4458441954605 \tabularnewline
0.92 & 1239.83607225329 & 38.3059939771707 \tabularnewline
0.93 & 1255.44110690519 & 34.4828126083624 \tabularnewline
0.94 & 1271.54544754721 & 31.9371057894419 \tabularnewline
0.95 & 1290.94596090533 & 34.1329325452537 \tabularnewline
0.96 & 1320.49168404841 & 48.3521189664954 \tabularnewline
0.97 & 1372.57122389973 & 82.722501499754 \tabularnewline
0.98 & 1459.416676333 & 125.378624573518 \tabularnewline
0.99 & 1571.03999646515 & 132.992013217137 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168994&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]607.27084595484[/C][C]172.490434202153[/C][/ROW]
[ROW][C]0.02[/C][C]722.089380679638[/C][C]72.5168981811601[/C][/ROW]
[ROW][C]0.03[/C][C]778.899452958904[/C][C]28.9974305092851[/C][/ROW]
[ROW][C]0.04[/C][C]802.182241213128[/C][C]18.6070870984396[/C][/ROW]
[ROW][C]0.05[/C][C]814.49258102201[/C][C]17.774550855695[/C][/ROW]
[ROW][C]0.06[/C][C]823.967979247925[/C][C]18.1288080368466[/C][/ROW]
[ROW][C]0.07[/C][C]832.465256805617[/C][C]17.8768647626016[/C][/ROW]
[ROW][C]0.08[/C][C]840.210078851713[/C][C]17.0345590192739[/C][/ROW]
[ROW][C]0.09[/C][C]847.230873480594[/C][C]16.2209218159045[/C][/ROW]
[ROW][C]0.1[/C][C]853.700050756145[/C][C]16.1194284465699[/C][/ROW]
[ROW][C]0.11[/C][C]859.947429193315[/C][C]17.1838872421612[/C][/ROW]
[ROW][C]0.12[/C][C]866.376179344846[/C][C]19.529212551665[/C][/ROW]
[ROW][C]0.13[/C][C]873.365395254562[/C][C]22.9513984008511[/C][/ROW]
[ROW][C]0.14[/C][C]881.187375124355[/C][C]26.9806599358685[/C][/ROW]
[ROW][C]0.15[/C][C]889.948592580539[/C][C]30.9641334013338[/C][/ROW]
[ROW][C]0.16[/C][C]899.56346308519[/C][C]34.2153666620801[/C][/ROW]
[ROW][C]0.17[/C][C]909.769815993203[/C][C]36.1725445451004[/C][/ROW]
[ROW][C]0.18[/C][C]920.185292748607[/C][C]36.5440208525292[/C][/ROW]
[ROW][C]0.19[/C][C]930.389446333342[/C][C]35.3596660922524[/C][/ROW]
[ROW][C]0.2[/C][C]940.007112690004[/C][C]32.9250642213131[/C][/ROW]
[ROW][C]0.21[/C][C]948.770214276147[/C][C]29.7183972284907[/C][/ROW]
[ROW][C]0.22[/C][C]956.54552209789[/C][C]26.2532605510166[/C][/ROW]
[ROW][C]0.23[/C][C]963.32864396349[/C][C]22.9709744123399[/C][/ROW]
[ROW][C]0.24[/C][C]969.213799446966[/C][C]20.1773306566489[/C][/ROW]
[ROW][C]0.25[/C][C]974.352420334525[/C][C]18.0159272106893[/C][/ROW]
[ROW][C]0.26[/C][C]978.912238135932[/C][C]16.4803299442005[/C][/ROW]
[ROW][C]0.27[/C][C]983.044735266795[/C][C]15.445837176266[/C][/ROW]
[ROW][C]0.28[/C][C]986.864795300408[/C][C]14.7251936789386[/C][/ROW]
[ROW][C]0.29[/C][C]990.443159111344[/C][C]14.1249868308874[/C][/ROW]
[ROW][C]0.3[/C][C]993.8100289302[/C][C]13.4931046657531[/C][/ROW]
[ROW][C]0.31[/C][C]996.96665536992[/C][C]12.7449043137136[/C][/ROW]
[ROW][C]0.32[/C][C]999.900869306147[/C][C]11.8702995717285[/C][/ROW]
[ROW][C]0.33[/C][C]1002.60234582358[/C][C]10.9222197410981[/C][/ROW]
[ROW][C]0.34[/C][C]1005.07401544088[/C][C]9.9951938863497[/C][/ROW]
[ROW][C]0.35[/C][C]1007.33740744383[/C][C]9.19745778489885[/C][/ROW]
[ROW][C]0.36[/C][C]1009.43150405432[/C][C]8.61618555421447[/C][/ROW]
[ROW][C]0.37[/C][C]1011.40640628652[/C][C]8.29371222060731[/C][/ROW]
[ROW][C]0.38[/C][C]1013.3142773977[/C][C]8.21377217440993[/C][/ROW]
[ROW][C]0.39[/C][C]1015.20035371854[/C][C]8.31434068349928[/C][/ROW]
[ROW][C]0.4[/C][C]1017.0963085023[/C][C]8.50765609285664[/C][/ROW]
[ROW][C]0.41[/C][C]1019.01720023532[/C][C]8.70695613420358[/C][/ROW]
[ROW][C]0.42[/C][C]1020.96204543903[/C][C]8.84396525638545[/C][/ROW]
[ROW][C]0.43[/C][C]1022.91711508182[/C][C]8.87597894108624[/C][/ROW]
[ROW][C]0.44[/C][C]1024.86060130787[/C][C]8.7835217814038[/C][/ROW]
[ROW][C]0.45[/C][C]1026.76737330364[/C][C]8.5686895965718[/C][/ROW]
[ROW][C]0.46[/C][C]1028.61299467271[/C][C]8.24501121262753[/C][/ROW]
[ROW][C]0.47[/C][C]1030.37676371724[/C][C]7.83673716526423[/C][/ROW]
[ROW][C]0.48[/C][C]1032.04401108522[/C][C]7.36994335352387[/C][/ROW]
[ROW][C]0.49[/C][C]1033.60807606485[/C][C]6.88546377079392[/C][/ROW]
[ROW][C]0.5[/C][C]1035.07224521634[/C][C]6.42337346142476[/C][/ROW]
[ROW][C]0.51[/C][C]1036.45157086552[/C][C]6.04362469616184[/C][/ROW]
[ROW][C]0.52[/C][C]1037.77407714774[/C][C]5.81560808641492[/C][/ROW]
[ROW][C]0.53[/C][C]1039.08060794337[/C][C]5.80744654863236[/C][/ROW]
[ROW][C]0.54[/C][C]1040.42261478415[/C][C]6.07685304772034[/C][/ROW]
[ROW][C]0.55[/C][C]1041.85755536895[/C][C]6.64125044246194[/C][/ROW]
[ROW][C]0.56[/C][C]1043.44218807708[/C][C]7.47085215073933[/C][/ROW]
[ROW][C]0.57[/C][C]1045.22472800474[/C][C]8.49617978965435[/C][/ROW]
[ROW][C]0.58[/C][C]1047.23736084332[/C][C]9.61100672334284[/C][/ROW]
[ROW][C]0.59[/C][C]1049.49079999542[/C][C]10.7044623142532[/C][/ROW]
[ROW][C]0.6[/C][C]1051.97230605816[/C][C]11.6628087284756[/C][/ROW]
[ROW][C]0.61[/C][C]1054.64787502426[/C][C]12.3964126953906[/C][/ROW]
[ROW][C]0.62[/C][C]1057.46829378721[/C][C]12.854445952941[/C][/ROW]
[ROW][C]0.63[/C][C]1060.37773482999[/C][C]13.0332966374698[/C][/ROW]
[ROW][C]0.64[/C][C]1063.32284861292[/C][C]12.9694960492753[/C][/ROW]
[ROW][C]0.65[/C][C]1066.26018836417[/C][C]12.7293667532005[/C][/ROW]
[ROW][C]0.66[/C][C]1069.1603660489[/C][C]12.3946381571333[/C][/ROW]
[ROW][C]0.67[/C][C]1072.00843633836[/C][C]12.0331876333707[/C][/ROW]
[ROW][C]0.68[/C][C]1074.80125677923[/C][C]11.6900751753241[/C][/ROW]
[ROW][C]0.69[/C][C]1077.54350723139[/C][C]11.3862680473273[/C][/ROW]
[ROW][C]0.7[/C][C]1080.24431137231[/C][C]11.1227961988649[/C][/ROW]
[ROW][C]0.71[/C][C]1082.91590743306[/C][C]10.8995379439927[/C][/ROW]
[ROW][C]0.72[/C][C]1085.57480318632[/C][C]10.7308386663084[/C][/ROW]
[ROW][C]0.73[/C][C]1088.2447626019[/C][C]10.6487368216786[/C][/ROW]
[ROW][C]0.74[/C][C]1090.96023757548[/C][C]10.7031838027651[/C][/ROW]
[ROW][C]0.75[/C][C]1093.76870633526[/C][C]10.9510423216677[/C][/ROW]
[ROW][C]0.76[/C][C]1096.73078520755[/C][C]11.4375864174683[/C][/ROW]
[ROW][C]0.77[/C][C]1099.9177621519[/C][C]12.1909128263164[/C][/ROW]
[ROW][C]0.78[/C][C]1103.40717998102[/C][C]13.2094812835773[/C][/ROW]
[ROW][C]0.79[/C][C]1107.27816146745[/C][C]14.4647853441442[/C][/ROW]
[ROW][C]0.8[/C][C]1111.60915160996[/C][C]15.9167384037203[/C][/ROW]
[ROW][C]0.81[/C][C]1116.48119428371[/C][C]17.5398670520939[/C][/ROW]
[ROW][C]0.82[/C][C]1121.98888153323[/C][C]19.355190814602[/C][/ROW]
[ROW][C]0.83[/C][C]1128.25772857237[/C][C]21.4608747497218[/C][/ROW]
[ROW][C]0.84[/C][C]1135.46078977886[/C][C]24.0212282072464[/C][/ROW]
[ROW][C]0.85[/C][C]1143.82081354082[/C][C]27.1961929085264[/C][/ROW]
[ROW][C]0.86[/C][C]1153.58179940645[/C][C]31.0040695174972[/C][/ROW]
[ROW][C]0.87[/C][C]1164.94120397936[/C][C]35.1656862451874[/C][/ROW]
[ROW][C]0.88[/C][C]1177.95367844588[/C][C]39.0578036212469[/C][/ROW]
[ROW][C]0.89[/C][C]1192.44327431707[/C][C]41.8407362216007[/C][/ROW]
[ROW][C]0.9[/C][C]1207.97878112465[/C][C]42.7484234352695[/C][/ROW]
[ROW][C]0.91[/C][C]1223.96055177731[/C][C]41.4458441954605[/C][/ROW]
[ROW][C]0.92[/C][C]1239.83607225329[/C][C]38.3059939771707[/C][/ROW]
[ROW][C]0.93[/C][C]1255.44110690519[/C][C]34.4828126083624[/C][/ROW]
[ROW][C]0.94[/C][C]1271.54544754721[/C][C]31.9371057894419[/C][/ROW]
[ROW][C]0.95[/C][C]1290.94596090533[/C][C]34.1329325452537[/C][/ROW]
[ROW][C]0.96[/C][C]1320.49168404841[/C][C]48.3521189664954[/C][/ROW]
[ROW][C]0.97[/C][C]1372.57122389973[/C][C]82.722501499754[/C][/ROW]
[ROW][C]0.98[/C][C]1459.416676333[/C][C]125.378624573518[/C][/ROW]
[ROW][C]0.99[/C][C]1571.03999646515[/C][C]132.992013217137[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168994&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168994&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
0.01607.27084595484172.490434202153
0.02722.08938067963872.5168981811601
0.03778.89945295890428.9974305092851
0.04802.18224121312818.6070870984396
0.05814.4925810220117.774550855695
0.06823.96797924792518.1288080368466
0.07832.46525680561717.8768647626016
0.08840.21007885171317.0345590192739
0.09847.23087348059416.2209218159045
0.1853.70005075614516.1194284465699
0.11859.94742919331517.1838872421612
0.12866.37617934484619.529212551665
0.13873.36539525456222.9513984008511
0.14881.18737512435526.9806599358685
0.15889.94859258053930.9641334013338
0.16899.5634630851934.2153666620801
0.17909.76981599320336.1725445451004
0.18920.18529274860736.5440208525292
0.19930.38944633334235.3596660922524
0.2940.00711269000432.9250642213131
0.21948.77021427614729.7183972284907
0.22956.5455220978926.2532605510166
0.23963.3286439634922.9709744123399
0.24969.21379944696620.1773306566489
0.25974.35242033452518.0159272106893
0.26978.91223813593216.4803299442005
0.27983.04473526679515.445837176266
0.28986.86479530040814.7251936789386
0.29990.44315911134414.1249868308874
0.3993.810028930213.4931046657531
0.31996.9666553699212.7449043137136
0.32999.90086930614711.8702995717285
0.331002.6023458235810.9222197410981
0.341005.074015440889.9951938863497
0.351007.337407443839.19745778489885
0.361009.431504054328.61618555421447
0.371011.406406286528.29371222060731
0.381013.31427739778.21377217440993
0.391015.200353718548.31434068349928
0.41017.09630850238.50765609285664
0.411019.017200235328.70695613420358
0.421020.962045439038.84396525638545
0.431022.917115081828.87597894108624
0.441024.860601307878.7835217814038
0.451026.767373303648.5686895965718
0.461028.612994672718.24501121262753
0.471030.376763717247.83673716526423
0.481032.044011085227.36994335352387
0.491033.608076064856.88546377079392
0.51035.072245216346.42337346142476
0.511036.451570865526.04362469616184
0.521037.774077147745.81560808641492
0.531039.080607943375.80744654863236
0.541040.422614784156.07685304772034
0.551041.857555368956.64125044246194
0.561043.442188077087.47085215073933
0.571045.224728004748.49617978965435
0.581047.237360843329.61100672334284
0.591049.4907999954210.7044623142532
0.61051.9723060581611.6628087284756
0.611054.6478750242612.3964126953906
0.621057.4682937872112.854445952941
0.631060.3777348299913.0332966374698
0.641063.3228486129212.9694960492753
0.651066.2601883641712.7293667532005
0.661069.160366048912.3946381571333
0.671072.0084363383612.0331876333707
0.681074.8012567792311.6900751753241
0.691077.5435072313911.3862680473273
0.71080.2443113723111.1227961988649
0.711082.9159074330610.8995379439927
0.721085.5748031863210.7308386663084
0.731088.244762601910.6487368216786
0.741090.9602375754810.7031838027651
0.751093.7687063352610.9510423216677
0.761096.7307852075511.4375864174683
0.771099.917762151912.1909128263164
0.781103.4071799810213.2094812835773
0.791107.2781614674514.4647853441442
0.81111.6091516099615.9167384037203
0.811116.4811942837117.5398670520939
0.821121.9888815332319.355190814602
0.831128.2577285723721.4608747497218
0.841135.4607897788624.0212282072464
0.851143.8208135408227.1961929085264
0.861153.5817994064531.0040695174972
0.871164.9412039793635.1656862451874
0.881177.9536784458839.0578036212469
0.891192.4432743170741.8407362216007
0.91207.9787811246542.7484234352695
0.911223.9605517773141.4458441954605
0.921239.8360722532938.3059939771707
0.931255.4411069051934.4828126083624
0.941271.5454475472131.9371057894419
0.951290.9459609053334.1329325452537
0.961320.4916840484148.3521189664954
0.971372.5712238997382.722501499754
0.981459.416676333125.378624573518
0.991571.03999646515132.992013217137


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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')