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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 computationMon, 02 Jun 2008 03:56:41 -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/Jun/02/t1212400669jcd29ndxiigguiq.htm/, Retrieved Sat, 18 May 2024 14:47:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13765, Retrieved Sat, 18 May 2024 14:47:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact313

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] [Harrell-Davis - g...] [2008-06-02 09:56:41] [b82ef19bb71ab1d2d730136b4505428a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10236
10893
10756
10940
10997
10827
10166
10186
10457
10368
10244
10511
10812
10738
10171
9721
9897
9828
9924
10371
10846
10413
10709
10662
10570
10297
10635
10872
10296
10383
10431
10574
10653
10805
10872
10625
10407
10463
10556
10646
10702
11353
11346
11451
11964
12574
13031
13812
14544
14931
14886
16005
17064
15168
16050
15839
15137
14954
15648
15305
15579
16348
15928
16171
15937
15713
15594
15683
16438
17032
17696
17745

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13765&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13765&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13765&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Harrell-Davis Quantiles
quantilesvaluestandard error
0.019755.8172109302197.86983015551
0.029809.9421964386397.323465676945
0.039869.78379879925109.713925444059
0.049929.62633557947125.956688117563
0.059987.80213303938135.233598564573
0.0610042.7735894862133.125237304521
0.0710092.6418970585121.761795783224
0.0810136.0916587745106.564975120779
0.0910172.976857495992.675152450625
0.110204.164586639682.818993914746
0.1110230.994631668677.1416205518654
0.1210254.769856890674.3063891506477
0.1310276.475890825272.7767139248175
0.1410296.727848339571.5450923607626
0.1510315.851928889670.1128014130119
0.1610334.008726511368.4503938229992
0.1710351.300446423666.8152578603712
0.1810367.839339825865.5323829023385
0.1910383.776615599264.9533525581769
0.210399.300934942365.2930487970516
0.2110414.618238448066.5895751140922
0.2210429.923911549568.7003455578852
0.2310445.376122202471.3593606886425
0.2410461.076412925274.1977858740928
0.2510477.060753970276.8693041691331
0.2610493.301626338479.0657616411373
0.2710509.719594478080.5820890596706
0.2810526.201428447081.3233203361075
0.2910542.621193051081.2846927093905
0.310558.860771546780.6041553955059
0.3110574.826887396679.4588031392355
0.3210590.462639182878.0961082119673
0.3310605.752673205576.7776522361576
0.3410620.722209770475.7077978858262
0.3510635.431078919175.0739815840254
0.3610649.964624015574.9684803137352
0.3710664.423755363675.4424759020027
0.3810678.916571650676.4885150453076
0.3910693.553827343178.0734800415735
0.410708.450137984380.1802207569596
0.4110723.732225467382.8635241912583
0.4210739.554768373886.3001787586269
0.4310756.123606575490.8404735094257
0.4410773.725228173497.0586857299786
0.4510792.7607092519105.733326114368
0.4610813.7816337339117.902965093368
0.4710837.5250127160134.747398805402
0.4810864.9438343174157.602685528472
0.4910897.2295589955187.83789702918
0.510935.8225742021226.757933531032
0.5110982.4063086068275.530928784922
0.5211038.8804333781335.210432488213
0.5311107.3085270557406.363254734066
0.5411189.8360757834489.145739486368
0.5511288.5761493088582.976361660228
0.5611405.4629514764686.429374910208
0.5711542.0779187427797.066716586981
0.5811699.4589654759911.383122045329
0.5911877.91013312931024.87682561085
0.612076.83499120221132.19501343179
0.6112294.62093737681227.53416018142
0.6212528.60127372171305.10744413700
0.6312775.11628404091359.76009289667
0.6413029.68320670341387.52842218128
0.6513287.26909708141386.2440096761
0.6613542.64268536271355.82497379120
0.6713790.76513924351298.41474870878
0.6814027.16911824581218.19191575054
0.6914248.27387792551120.90006367637
0.714451.59286869801013.16610742522
0.7114635.8082182755901.719938147031
0.7214800.7101218168792.625949504655
0.7314947.0231451674690.710118006134
0.7415076.1600272214599.164291442299
0.7515189.9522578316519.503988813721
0.7615290.4037041355451.782425055579
0.7715379.5004283567395.055449622586
0.7815459.0911380061347.851756939195
0.7915530.8345294271308.721868426456
0.815596.1976648148276.455787806662
0.8115656.4864188626250.144244216786
0.8215712.8942014394229.123685807909
0.8315766.5645292844212.884038884429
0.8415818.6710161261201.155870647327
0.8515870.5204543094194.029475412958
0.8615923.6791947995192.073498483109
0.8715980.1109743293196.401509035674
0.8816042.2974271489208.446146087657
0.8916113.2926642871229.475863666359
0.916196.6475526718260.065914600266
0.9116296.1485185374299.321683081735
0.9216415.3776803621344.021316999689
0.9316557.1967206167388.334175683941
0.9416723.2316894355425.366215835719
0.9516913.0405535041450.126839970956
0.9617121.9845972179458.569640144652
0.9717337.0834993067436.167997760756
0.9817533.1883606569350.937622011668
0.9917676.8676903525192.223944256014

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 9755.81721093021 & 97.86983015551 \tabularnewline
0.02 & 9809.94219643863 & 97.323465676945 \tabularnewline
0.03 & 9869.78379879925 & 109.713925444059 \tabularnewline
0.04 & 9929.62633557947 & 125.956688117563 \tabularnewline
0.05 & 9987.80213303938 & 135.233598564573 \tabularnewline
0.06 & 10042.7735894862 & 133.125237304521 \tabularnewline
0.07 & 10092.6418970585 & 121.761795783224 \tabularnewline
0.08 & 10136.0916587745 & 106.564975120779 \tabularnewline
0.09 & 10172.9768574959 & 92.675152450625 \tabularnewline
0.1 & 10204.1645866396 & 82.818993914746 \tabularnewline
0.11 & 10230.9946316686 & 77.1416205518654 \tabularnewline
0.12 & 10254.7698568906 & 74.3063891506477 \tabularnewline
0.13 & 10276.4758908252 & 72.7767139248175 \tabularnewline
0.14 & 10296.7278483395 & 71.5450923607626 \tabularnewline
0.15 & 10315.8519288896 & 70.1128014130119 \tabularnewline
0.16 & 10334.0087265113 & 68.4503938229992 \tabularnewline
0.17 & 10351.3004464236 & 66.8152578603712 \tabularnewline
0.18 & 10367.8393398258 & 65.5323829023385 \tabularnewline
0.19 & 10383.7766155992 & 64.9533525581769 \tabularnewline
0.2 & 10399.3009349423 & 65.2930487970516 \tabularnewline
0.21 & 10414.6182384480 & 66.5895751140922 \tabularnewline
0.22 & 10429.9239115495 & 68.7003455578852 \tabularnewline
0.23 & 10445.3761222024 & 71.3593606886425 \tabularnewline
0.24 & 10461.0764129252 & 74.1977858740928 \tabularnewline
0.25 & 10477.0607539702 & 76.8693041691331 \tabularnewline
0.26 & 10493.3016263384 & 79.0657616411373 \tabularnewline
0.27 & 10509.7195944780 & 80.5820890596706 \tabularnewline
0.28 & 10526.2014284470 & 81.3233203361075 \tabularnewline
0.29 & 10542.6211930510 & 81.2846927093905 \tabularnewline
0.3 & 10558.8607715467 & 80.6041553955059 \tabularnewline
0.31 & 10574.8268873966 & 79.4588031392355 \tabularnewline
0.32 & 10590.4626391828 & 78.0961082119673 \tabularnewline
0.33 & 10605.7526732055 & 76.7776522361576 \tabularnewline
0.34 & 10620.7222097704 & 75.7077978858262 \tabularnewline
0.35 & 10635.4310789191 & 75.0739815840254 \tabularnewline
0.36 & 10649.9646240155 & 74.9684803137352 \tabularnewline
0.37 & 10664.4237553636 & 75.4424759020027 \tabularnewline
0.38 & 10678.9165716506 & 76.4885150453076 \tabularnewline
0.39 & 10693.5538273431 & 78.0734800415735 \tabularnewline
0.4 & 10708.4501379843 & 80.1802207569596 \tabularnewline
0.41 & 10723.7322254673 & 82.8635241912583 \tabularnewline
0.42 & 10739.5547683738 & 86.3001787586269 \tabularnewline
0.43 & 10756.1236065754 & 90.8404735094257 \tabularnewline
0.44 & 10773.7252281734 & 97.0586857299786 \tabularnewline
0.45 & 10792.7607092519 & 105.733326114368 \tabularnewline
0.46 & 10813.7816337339 & 117.902965093368 \tabularnewline
0.47 & 10837.5250127160 & 134.747398805402 \tabularnewline
0.48 & 10864.9438343174 & 157.602685528472 \tabularnewline
0.49 & 10897.2295589955 & 187.83789702918 \tabularnewline
0.5 & 10935.8225742021 & 226.757933531032 \tabularnewline
0.51 & 10982.4063086068 & 275.530928784922 \tabularnewline
0.52 & 11038.8804333781 & 335.210432488213 \tabularnewline
0.53 & 11107.3085270557 & 406.363254734066 \tabularnewline
0.54 & 11189.8360757834 & 489.145739486368 \tabularnewline
0.55 & 11288.5761493088 & 582.976361660228 \tabularnewline
0.56 & 11405.4629514764 & 686.429374910208 \tabularnewline
0.57 & 11542.0779187427 & 797.066716586981 \tabularnewline
0.58 & 11699.4589654759 & 911.383122045329 \tabularnewline
0.59 & 11877.9101331293 & 1024.87682561085 \tabularnewline
0.6 & 12076.8349912022 & 1132.19501343179 \tabularnewline
0.61 & 12294.6209373768 & 1227.53416018142 \tabularnewline
0.62 & 12528.6012737217 & 1305.10744413700 \tabularnewline
0.63 & 12775.1162840409 & 1359.76009289667 \tabularnewline
0.64 & 13029.6832067034 & 1387.52842218128 \tabularnewline
0.65 & 13287.2690970814 & 1386.2440096761 \tabularnewline
0.66 & 13542.6426853627 & 1355.82497379120 \tabularnewline
0.67 & 13790.7651392435 & 1298.41474870878 \tabularnewline
0.68 & 14027.1691182458 & 1218.19191575054 \tabularnewline
0.69 & 14248.2738779255 & 1120.90006367637 \tabularnewline
0.7 & 14451.5928686980 & 1013.16610742522 \tabularnewline
0.71 & 14635.8082182755 & 901.719938147031 \tabularnewline
0.72 & 14800.7101218168 & 792.625949504655 \tabularnewline
0.73 & 14947.0231451674 & 690.710118006134 \tabularnewline
0.74 & 15076.1600272214 & 599.164291442299 \tabularnewline
0.75 & 15189.9522578316 & 519.503988813721 \tabularnewline
0.76 & 15290.4037041355 & 451.782425055579 \tabularnewline
0.77 & 15379.5004283567 & 395.055449622586 \tabularnewline
0.78 & 15459.0911380061 & 347.851756939195 \tabularnewline
0.79 & 15530.8345294271 & 308.721868426456 \tabularnewline
0.8 & 15596.1976648148 & 276.455787806662 \tabularnewline
0.81 & 15656.4864188626 & 250.144244216786 \tabularnewline
0.82 & 15712.8942014394 & 229.123685807909 \tabularnewline
0.83 & 15766.5645292844 & 212.884038884429 \tabularnewline
0.84 & 15818.6710161261 & 201.155870647327 \tabularnewline
0.85 & 15870.5204543094 & 194.029475412958 \tabularnewline
0.86 & 15923.6791947995 & 192.073498483109 \tabularnewline
0.87 & 15980.1109743293 & 196.401509035674 \tabularnewline
0.88 & 16042.2974271489 & 208.446146087657 \tabularnewline
0.89 & 16113.2926642871 & 229.475863666359 \tabularnewline
0.9 & 16196.6475526718 & 260.065914600266 \tabularnewline
0.91 & 16296.1485185374 & 299.321683081735 \tabularnewline
0.92 & 16415.3776803621 & 344.021316999689 \tabularnewline
0.93 & 16557.1967206167 & 388.334175683941 \tabularnewline
0.94 & 16723.2316894355 & 425.366215835719 \tabularnewline
0.95 & 16913.0405535041 & 450.126839970956 \tabularnewline
0.96 & 17121.9845972179 & 458.569640144652 \tabularnewline
0.97 & 17337.0834993067 & 436.167997760756 \tabularnewline
0.98 & 17533.1883606569 & 350.937622011668 \tabularnewline
0.99 & 17676.8676903525 & 192.223944256014 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13765&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]9755.81721093021[/C][C]97.86983015551[/C][/ROW]
[ROW][C]0.02[/C][C]9809.94219643863[/C][C]97.323465676945[/C][/ROW]
[ROW][C]0.03[/C][C]9869.78379879925[/C][C]109.713925444059[/C][/ROW]
[ROW][C]0.04[/C][C]9929.62633557947[/C][C]125.956688117563[/C][/ROW]
[ROW][C]0.05[/C][C]9987.80213303938[/C][C]135.233598564573[/C][/ROW]
[ROW][C]0.06[/C][C]10042.7735894862[/C][C]133.125237304521[/C][/ROW]
[ROW][C]0.07[/C][C]10092.6418970585[/C][C]121.761795783224[/C][/ROW]
[ROW][C]0.08[/C][C]10136.0916587745[/C][C]106.564975120779[/C][/ROW]
[ROW][C]0.09[/C][C]10172.9768574959[/C][C]92.675152450625[/C][/ROW]
[ROW][C]0.1[/C][C]10204.1645866396[/C][C]82.818993914746[/C][/ROW]
[ROW][C]0.11[/C][C]10230.9946316686[/C][C]77.1416205518654[/C][/ROW]
[ROW][C]0.12[/C][C]10254.7698568906[/C][C]74.3063891506477[/C][/ROW]
[ROW][C]0.13[/C][C]10276.4758908252[/C][C]72.7767139248175[/C][/ROW]
[ROW][C]0.14[/C][C]10296.7278483395[/C][C]71.5450923607626[/C][/ROW]
[ROW][C]0.15[/C][C]10315.8519288896[/C][C]70.1128014130119[/C][/ROW]
[ROW][C]0.16[/C][C]10334.0087265113[/C][C]68.4503938229992[/C][/ROW]
[ROW][C]0.17[/C][C]10351.3004464236[/C][C]66.8152578603712[/C][/ROW]
[ROW][C]0.18[/C][C]10367.8393398258[/C][C]65.5323829023385[/C][/ROW]
[ROW][C]0.19[/C][C]10383.7766155992[/C][C]64.9533525581769[/C][/ROW]
[ROW][C]0.2[/C][C]10399.3009349423[/C][C]65.2930487970516[/C][/ROW]
[ROW][C]0.21[/C][C]10414.6182384480[/C][C]66.5895751140922[/C][/ROW]
[ROW][C]0.22[/C][C]10429.9239115495[/C][C]68.7003455578852[/C][/ROW]
[ROW][C]0.23[/C][C]10445.3761222024[/C][C]71.3593606886425[/C][/ROW]
[ROW][C]0.24[/C][C]10461.0764129252[/C][C]74.1977858740928[/C][/ROW]
[ROW][C]0.25[/C][C]10477.0607539702[/C][C]76.8693041691331[/C][/ROW]
[ROW][C]0.26[/C][C]10493.3016263384[/C][C]79.0657616411373[/C][/ROW]
[ROW][C]0.27[/C][C]10509.7195944780[/C][C]80.5820890596706[/C][/ROW]
[ROW][C]0.28[/C][C]10526.2014284470[/C][C]81.3233203361075[/C][/ROW]
[ROW][C]0.29[/C][C]10542.6211930510[/C][C]81.2846927093905[/C][/ROW]
[ROW][C]0.3[/C][C]10558.8607715467[/C][C]80.6041553955059[/C][/ROW]
[ROW][C]0.31[/C][C]10574.8268873966[/C][C]79.4588031392355[/C][/ROW]
[ROW][C]0.32[/C][C]10590.4626391828[/C][C]78.0961082119673[/C][/ROW]
[ROW][C]0.33[/C][C]10605.7526732055[/C][C]76.7776522361576[/C][/ROW]
[ROW][C]0.34[/C][C]10620.7222097704[/C][C]75.7077978858262[/C][/ROW]
[ROW][C]0.35[/C][C]10635.4310789191[/C][C]75.0739815840254[/C][/ROW]
[ROW][C]0.36[/C][C]10649.9646240155[/C][C]74.9684803137352[/C][/ROW]
[ROW][C]0.37[/C][C]10664.4237553636[/C][C]75.4424759020027[/C][/ROW]
[ROW][C]0.38[/C][C]10678.9165716506[/C][C]76.4885150453076[/C][/ROW]
[ROW][C]0.39[/C][C]10693.5538273431[/C][C]78.0734800415735[/C][/ROW]
[ROW][C]0.4[/C][C]10708.4501379843[/C][C]80.1802207569596[/C][/ROW]
[ROW][C]0.41[/C][C]10723.7322254673[/C][C]82.8635241912583[/C][/ROW]
[ROW][C]0.42[/C][C]10739.5547683738[/C][C]86.3001787586269[/C][/ROW]
[ROW][C]0.43[/C][C]10756.1236065754[/C][C]90.8404735094257[/C][/ROW]
[ROW][C]0.44[/C][C]10773.7252281734[/C][C]97.0586857299786[/C][/ROW]
[ROW][C]0.45[/C][C]10792.7607092519[/C][C]105.733326114368[/C][/ROW]
[ROW][C]0.46[/C][C]10813.7816337339[/C][C]117.902965093368[/C][/ROW]
[ROW][C]0.47[/C][C]10837.5250127160[/C][C]134.747398805402[/C][/ROW]
[ROW][C]0.48[/C][C]10864.9438343174[/C][C]157.602685528472[/C][/ROW]
[ROW][C]0.49[/C][C]10897.2295589955[/C][C]187.83789702918[/C][/ROW]
[ROW][C]0.5[/C][C]10935.8225742021[/C][C]226.757933531032[/C][/ROW]
[ROW][C]0.51[/C][C]10982.4063086068[/C][C]275.530928784922[/C][/ROW]
[ROW][C]0.52[/C][C]11038.8804333781[/C][C]335.210432488213[/C][/ROW]
[ROW][C]0.53[/C][C]11107.3085270557[/C][C]406.363254734066[/C][/ROW]
[ROW][C]0.54[/C][C]11189.8360757834[/C][C]489.145739486368[/C][/ROW]
[ROW][C]0.55[/C][C]11288.5761493088[/C][C]582.976361660228[/C][/ROW]
[ROW][C]0.56[/C][C]11405.4629514764[/C][C]686.429374910208[/C][/ROW]
[ROW][C]0.57[/C][C]11542.0779187427[/C][C]797.066716586981[/C][/ROW]
[ROW][C]0.58[/C][C]11699.4589654759[/C][C]911.383122045329[/C][/ROW]
[ROW][C]0.59[/C][C]11877.9101331293[/C][C]1024.87682561085[/C][/ROW]
[ROW][C]0.6[/C][C]12076.8349912022[/C][C]1132.19501343179[/C][/ROW]
[ROW][C]0.61[/C][C]12294.6209373768[/C][C]1227.53416018142[/C][/ROW]
[ROW][C]0.62[/C][C]12528.6012737217[/C][C]1305.10744413700[/C][/ROW]
[ROW][C]0.63[/C][C]12775.1162840409[/C][C]1359.76009289667[/C][/ROW]
[ROW][C]0.64[/C][C]13029.6832067034[/C][C]1387.52842218128[/C][/ROW]
[ROW][C]0.65[/C][C]13287.2690970814[/C][C]1386.2440096761[/C][/ROW]
[ROW][C]0.66[/C][C]13542.6426853627[/C][C]1355.82497379120[/C][/ROW]
[ROW][C]0.67[/C][C]13790.7651392435[/C][C]1298.41474870878[/C][/ROW]
[ROW][C]0.68[/C][C]14027.1691182458[/C][C]1218.19191575054[/C][/ROW]
[ROW][C]0.69[/C][C]14248.2738779255[/C][C]1120.90006367637[/C][/ROW]
[ROW][C]0.7[/C][C]14451.5928686980[/C][C]1013.16610742522[/C][/ROW]
[ROW][C]0.71[/C][C]14635.8082182755[/C][C]901.719938147031[/C][/ROW]
[ROW][C]0.72[/C][C]14800.7101218168[/C][C]792.625949504655[/C][/ROW]
[ROW][C]0.73[/C][C]14947.0231451674[/C][C]690.710118006134[/C][/ROW]
[ROW][C]0.74[/C][C]15076.1600272214[/C][C]599.164291442299[/C][/ROW]
[ROW][C]0.75[/C][C]15189.9522578316[/C][C]519.503988813721[/C][/ROW]
[ROW][C]0.76[/C][C]15290.4037041355[/C][C]451.782425055579[/C][/ROW]
[ROW][C]0.77[/C][C]15379.5004283567[/C][C]395.055449622586[/C][/ROW]
[ROW][C]0.78[/C][C]15459.0911380061[/C][C]347.851756939195[/C][/ROW]
[ROW][C]0.79[/C][C]15530.8345294271[/C][C]308.721868426456[/C][/ROW]
[ROW][C]0.8[/C][C]15596.1976648148[/C][C]276.455787806662[/C][/ROW]
[ROW][C]0.81[/C][C]15656.4864188626[/C][C]250.144244216786[/C][/ROW]
[ROW][C]0.82[/C][C]15712.8942014394[/C][C]229.123685807909[/C][/ROW]
[ROW][C]0.83[/C][C]15766.5645292844[/C][C]212.884038884429[/C][/ROW]
[ROW][C]0.84[/C][C]15818.6710161261[/C][C]201.155870647327[/C][/ROW]
[ROW][C]0.85[/C][C]15870.5204543094[/C][C]194.029475412958[/C][/ROW]
[ROW][C]0.86[/C][C]15923.6791947995[/C][C]192.073498483109[/C][/ROW]
[ROW][C]0.87[/C][C]15980.1109743293[/C][C]196.401509035674[/C][/ROW]
[ROW][C]0.88[/C][C]16042.2974271489[/C][C]208.446146087657[/C][/ROW]
[ROW][C]0.89[/C][C]16113.2926642871[/C][C]229.475863666359[/C][/ROW]
[ROW][C]0.9[/C][C]16196.6475526718[/C][C]260.065914600266[/C][/ROW]
[ROW][C]0.91[/C][C]16296.1485185374[/C][C]299.321683081735[/C][/ROW]
[ROW][C]0.92[/C][C]16415.3776803621[/C][C]344.021316999689[/C][/ROW]
[ROW][C]0.93[/C][C]16557.1967206167[/C][C]388.334175683941[/C][/ROW]
[ROW][C]0.94[/C][C]16723.2316894355[/C][C]425.366215835719[/C][/ROW]
[ROW][C]0.95[/C][C]16913.0405535041[/C][C]450.126839970956[/C][/ROW]
[ROW][C]0.96[/C][C]17121.9845972179[/C][C]458.569640144652[/C][/ROW]
[ROW][C]0.97[/C][C]17337.0834993067[/C][C]436.167997760756[/C][/ROW]
[ROW][C]0.98[/C][C]17533.1883606569[/C][C]350.937622011668[/C][/ROW]
[ROW][C]0.99[/C][C]17676.8676903525[/C][C]192.223944256014[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13765&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13765&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
0.019755.8172109302197.86983015551
0.029809.9421964386397.323465676945
0.039869.78379879925109.713925444059
0.049929.62633557947125.956688117563
0.059987.80213303938135.233598564573
0.0610042.7735894862133.125237304521
0.0710092.6418970585121.761795783224
0.0810136.0916587745106.564975120779
0.0910172.976857495992.675152450625
0.110204.164586639682.818993914746
0.1110230.994631668677.1416205518654
0.1210254.769856890674.3063891506477
0.1310276.475890825272.7767139248175
0.1410296.727848339571.5450923607626
0.1510315.851928889670.1128014130119
0.1610334.008726511368.4503938229992
0.1710351.300446423666.8152578603712
0.1810367.839339825865.5323829023385
0.1910383.776615599264.9533525581769
0.210399.300934942365.2930487970516
0.2110414.618238448066.5895751140922
0.2210429.923911549568.7003455578852
0.2310445.376122202471.3593606886425
0.2410461.076412925274.1977858740928
0.2510477.060753970276.8693041691331
0.2610493.301626338479.0657616411373
0.2710509.719594478080.5820890596706
0.2810526.201428447081.3233203361075
0.2910542.621193051081.2846927093905
0.310558.860771546780.6041553955059
0.3110574.826887396679.4588031392355
0.3210590.462639182878.0961082119673
0.3310605.752673205576.7776522361576
0.3410620.722209770475.7077978858262
0.3510635.431078919175.0739815840254
0.3610649.964624015574.9684803137352
0.3710664.423755363675.4424759020027
0.3810678.916571650676.4885150453076
0.3910693.553827343178.0734800415735
0.410708.450137984380.1802207569596
0.4110723.732225467382.8635241912583
0.4210739.554768373886.3001787586269
0.4310756.123606575490.8404735094257
0.4410773.725228173497.0586857299786
0.4510792.7607092519105.733326114368
0.4610813.7816337339117.902965093368
0.4710837.5250127160134.747398805402
0.4810864.9438343174157.602685528472
0.4910897.2295589955187.83789702918
0.510935.8225742021226.757933531032
0.5110982.4063086068275.530928784922
0.5211038.8804333781335.210432488213
0.5311107.3085270557406.363254734066
0.5411189.8360757834489.145739486368
0.5511288.5761493088582.976361660228
0.5611405.4629514764686.429374910208
0.5711542.0779187427797.066716586981
0.5811699.4589654759911.383122045329
0.5911877.91013312931024.87682561085
0.612076.83499120221132.19501343179
0.6112294.62093737681227.53416018142
0.6212528.60127372171305.10744413700
0.6312775.11628404091359.76009289667
0.6413029.68320670341387.52842218128
0.6513287.26909708141386.2440096761
0.6613542.64268536271355.82497379120
0.6713790.76513924351298.41474870878
0.6814027.16911824581218.19191575054
0.6914248.27387792551120.90006367637
0.714451.59286869801013.16610742522
0.7114635.8082182755901.719938147031
0.7214800.7101218168792.625949504655
0.7314947.0231451674690.710118006134
0.7415076.1600272214599.164291442299
0.7515189.9522578316519.503988813721
0.7615290.4037041355451.782425055579
0.7715379.5004283567395.055449622586
0.7815459.0911380061347.851756939195
0.7915530.8345294271308.721868426456
0.815596.1976648148276.455787806662
0.8115656.4864188626250.144244216786
0.8215712.8942014394229.123685807909
0.8315766.5645292844212.884038884429
0.8415818.6710161261201.155870647327
0.8515870.5204543094194.029475412958
0.8615923.6791947995192.073498483109
0.8715980.1109743293196.401509035674
0.8816042.2974271489208.446146087657
0.8916113.2926642871229.475863666359
0.916196.6475526718260.065914600266
0.9116296.1485185374299.321683081735
0.9216415.3776803621344.021316999689
0.9316557.1967206167388.334175683941
0.9416723.2316894355425.366215835719
0.9516913.0405535041450.126839970956
0.9617121.9845972179458.569640144652
0.9717337.0834993067436.167997760756
0.9817533.1883606569350.937622011668
0.9917676.8676903525192.223944256014


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')