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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, 12 Dec 2011 04:59:04 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/12/t1323684146swckn3vuc6zzh9c.htm/, Retrieved Fri, 03 May 2024 12:09:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153888, Retrieved Fri, 03 May 2024 12:09:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDG201142
Estimated Impact105

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] [percielen inschri...] [2011-12-12 09:59:04] [23c029da43917b1445ec911a9179ae8a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
589,85
589,85
589,85
589,85
589,85
589,85
589,85
589,85
589,85
599,12
599,12
599,12
599
599
599
599
599
599
599
599
599
617,06
617,06
617,06
617,06
617,06
617,06
617,06
617,06
617,06
617,06
617,06
617,06
628,18
628,18
628,18
628,18
628,18
628,18
628,18
628,18
628,18
628,18
628,18
628,18
641,08
641,08
641,08
641,08
641,08
641,08
641,08
641,08
641,08
641,08
641,08
641,08
668,21
668,21
668,21
668,21
668,21
668,21
668,21
668,21
668,21
668,21
668,21
668,21
665,27
665,27
665,27

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' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153888&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153888&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153888&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' @ jenkins.wessa.net






Harrell-Davis Quantiles
quantilesvaluestandard error
0.01589.850253236650.0013606870611333
0.02589.8521045719380.0102051529584997
0.03589.8599668511680.0425214706604156
0.04589.8843480880570.128755013159738
0.05589.9448432701320.310406735821034
0.06590.0710158362920.627616906947734
0.07590.299151090611.09790437245193
0.08590.6643942785171.69929566666208
0.09591.1901905097522.36324621532467
0.1591.8788330164192.988944082518
0.11592.707064998343.47045999535181
0.12593.6288612800133.72922355659422
0.13594.5846911187843.73358312288261
0.14595.5141873341343.50756509102746
0.15596.3682760712283.11832297381398
0.16597.1175960773192.6566621005116
0.17597.7557891825892.22079193994758
0.18598.298025982921.90524269642378
0.19598.7762464052991.79681382209189
0.2599.2328503610331.94609160936344
0.21599.7142031343282.34448238807786
0.22600.2647325492972.94340139248091
0.23600.9219294307933.6852263835085
0.24601.712363473394.50615110568799
0.25602.648849024615.33355397709516
0.26603.7289933972956.09227204332232
0.27604.9353873975746.70960387353227
0.28606.2375759191337.12669781712311
0.29607.5956879606347.30676352259788
0.3608.965291959877.23984560716225
0.31610.3027812765486.94542625648895
0.32611.5704735708386.46605171770647
0.33612.7406640520425.86414484180771
0.34613.7980858252725.21152735151977
0.35614.7405370418654.58033070486382
0.36615.5777535780124.03638529039765
0.37616.3288672951573.63398734909483
0.38617.0189520106663.4063500937085
0.39617.6752138787953.35816837238739
0.4618.3233476981953.46321301699705
0.41618.9844859336253.67407562188237
0.42619.6730426060753.93596077766668
0.43620.3956209642714.19612961805018
0.44621.151023774434.41044930423598
0.45621.9312839943144.5448562602489
0.46622.723526385894.57954594863739
0.47623.5123843110694.5088614846967
0.48624.2826397058254.34216514678512
0.49625.0217365012514.10208560737502
0.5625.7218426512253.8215403566818
0.51626.3812007379543.54159672745
0.52627.0046024390143.30619100299544
0.53627.6029342567473.157979702047
0.54628.1918563968953.12960555941353
0.55628.7897812916123.23486699844343
0.56629.4154040640863.46465027473067
0.57630.0850978525643.78852398695363
0.58630.8105168873454.16437046507824
0.59631.5967440207064.54471612120581
0.6632.4412723292534.88098312734033
0.61633.3340212938795.13022952748658
0.62634.2584627284745.26076346898231
0.63635.1937847863315.25391066750801
0.64636.1178762663325.10842240839949
0.65637.0107926891524.8429090430481
0.66637.8582897473314.49316588946641
0.67638.6549865786314.11199502250418
0.68639.4067447933333.76575947928778
0.69640.1319037077133.53385472773597
0.7640.861082818253.50049322221392
0.71641.6353463921543.73369890292411
0.72642.5026378802544.25950541146783
0.73643.5125629988675.05443117188909
0.74644.7098545712926.05755339430143
0.75646.1271837081547.17868721433153
0.76647.7783322753188.30619494591645
0.77649.6529977389829.31363010159972
0.78651.71452363075910.0733652379867
0.79653.90152681873910.4789062057666
0.8656.13371078237110.460989457479
0.81658.3212329711210.0039843781106
0.82660.37608052569.14979033290874
0.83662.2233004861737.98998282778411
0.84663.8098635207916.65034617535037
0.85665.1094800826225.26495387136512
0.86666.1226870139243.95563496041364
0.87666.8726666739112.81249205849886
0.88667.3981908941551.88606701235073
0.89667.7455356139291.18773185408457
0.9667.9611145100530.698760634912474
0.91668.0860504069330.381312584829681
0.92668.1531798613510.191454377082291
0.93668.1863181439380.0871069143491941
0.94668.2011706730040.035662453861663
0.95668.2071203002520.0126251867805593
0.96668.2092046529950.00381980130682075
0.97668.2098233817860.000954243807827248
0.98668.2099713621570.000191665076511808
0.99668.2099973454260

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 589.85025323665 & 0.0013606870611333 \tabularnewline
0.02 & 589.852104571938 & 0.0102051529584997 \tabularnewline
0.03 & 589.859966851168 & 0.0425214706604156 \tabularnewline
0.04 & 589.884348088057 & 0.128755013159738 \tabularnewline
0.05 & 589.944843270132 & 0.310406735821034 \tabularnewline
0.06 & 590.071015836292 & 0.627616906947734 \tabularnewline
0.07 & 590.29915109061 & 1.09790437245193 \tabularnewline
0.08 & 590.664394278517 & 1.69929566666208 \tabularnewline
0.09 & 591.190190509752 & 2.36324621532467 \tabularnewline
0.1 & 591.878833016419 & 2.988944082518 \tabularnewline
0.11 & 592.70706499834 & 3.47045999535181 \tabularnewline
0.12 & 593.628861280013 & 3.72922355659422 \tabularnewline
0.13 & 594.584691118784 & 3.73358312288261 \tabularnewline
0.14 & 595.514187334134 & 3.50756509102746 \tabularnewline
0.15 & 596.368276071228 & 3.11832297381398 \tabularnewline
0.16 & 597.117596077319 & 2.6566621005116 \tabularnewline
0.17 & 597.755789182589 & 2.22079193994758 \tabularnewline
0.18 & 598.29802598292 & 1.90524269642378 \tabularnewline
0.19 & 598.776246405299 & 1.79681382209189 \tabularnewline
0.2 & 599.232850361033 & 1.94609160936344 \tabularnewline
0.21 & 599.714203134328 & 2.34448238807786 \tabularnewline
0.22 & 600.264732549297 & 2.94340139248091 \tabularnewline
0.23 & 600.921929430793 & 3.6852263835085 \tabularnewline
0.24 & 601.71236347339 & 4.50615110568799 \tabularnewline
0.25 & 602.64884902461 & 5.33355397709516 \tabularnewline
0.26 & 603.728993397295 & 6.09227204332232 \tabularnewline
0.27 & 604.935387397574 & 6.70960387353227 \tabularnewline
0.28 & 606.237575919133 & 7.12669781712311 \tabularnewline
0.29 & 607.595687960634 & 7.30676352259788 \tabularnewline
0.3 & 608.96529195987 & 7.23984560716225 \tabularnewline
0.31 & 610.302781276548 & 6.94542625648895 \tabularnewline
0.32 & 611.570473570838 & 6.46605171770647 \tabularnewline
0.33 & 612.740664052042 & 5.86414484180771 \tabularnewline
0.34 & 613.798085825272 & 5.21152735151977 \tabularnewline
0.35 & 614.740537041865 & 4.58033070486382 \tabularnewline
0.36 & 615.577753578012 & 4.03638529039765 \tabularnewline
0.37 & 616.328867295157 & 3.63398734909483 \tabularnewline
0.38 & 617.018952010666 & 3.4063500937085 \tabularnewline
0.39 & 617.675213878795 & 3.35816837238739 \tabularnewline
0.4 & 618.323347698195 & 3.46321301699705 \tabularnewline
0.41 & 618.984485933625 & 3.67407562188237 \tabularnewline
0.42 & 619.673042606075 & 3.93596077766668 \tabularnewline
0.43 & 620.395620964271 & 4.19612961805018 \tabularnewline
0.44 & 621.15102377443 & 4.41044930423598 \tabularnewline
0.45 & 621.931283994314 & 4.5448562602489 \tabularnewline
0.46 & 622.72352638589 & 4.57954594863739 \tabularnewline
0.47 & 623.512384311069 & 4.5088614846967 \tabularnewline
0.48 & 624.282639705825 & 4.34216514678512 \tabularnewline
0.49 & 625.021736501251 & 4.10208560737502 \tabularnewline
0.5 & 625.721842651225 & 3.8215403566818 \tabularnewline
0.51 & 626.381200737954 & 3.54159672745 \tabularnewline
0.52 & 627.004602439014 & 3.30619100299544 \tabularnewline
0.53 & 627.602934256747 & 3.157979702047 \tabularnewline
0.54 & 628.191856396895 & 3.12960555941353 \tabularnewline
0.55 & 628.789781291612 & 3.23486699844343 \tabularnewline
0.56 & 629.415404064086 & 3.46465027473067 \tabularnewline
0.57 & 630.085097852564 & 3.78852398695363 \tabularnewline
0.58 & 630.810516887345 & 4.16437046507824 \tabularnewline
0.59 & 631.596744020706 & 4.54471612120581 \tabularnewline
0.6 & 632.441272329253 & 4.88098312734033 \tabularnewline
0.61 & 633.334021293879 & 5.13022952748658 \tabularnewline
0.62 & 634.258462728474 & 5.26076346898231 \tabularnewline
0.63 & 635.193784786331 & 5.25391066750801 \tabularnewline
0.64 & 636.117876266332 & 5.10842240839949 \tabularnewline
0.65 & 637.010792689152 & 4.8429090430481 \tabularnewline
0.66 & 637.858289747331 & 4.49316588946641 \tabularnewline
0.67 & 638.654986578631 & 4.11199502250418 \tabularnewline
0.68 & 639.406744793333 & 3.76575947928778 \tabularnewline
0.69 & 640.131903707713 & 3.53385472773597 \tabularnewline
0.7 & 640.86108281825 & 3.50049322221392 \tabularnewline
0.71 & 641.635346392154 & 3.73369890292411 \tabularnewline
0.72 & 642.502637880254 & 4.25950541146783 \tabularnewline
0.73 & 643.512562998867 & 5.05443117188909 \tabularnewline
0.74 & 644.709854571292 & 6.05755339430143 \tabularnewline
0.75 & 646.127183708154 & 7.17868721433153 \tabularnewline
0.76 & 647.778332275318 & 8.30619494591645 \tabularnewline
0.77 & 649.652997738982 & 9.31363010159972 \tabularnewline
0.78 & 651.714523630759 & 10.0733652379867 \tabularnewline
0.79 & 653.901526818739 & 10.4789062057666 \tabularnewline
0.8 & 656.133710782371 & 10.460989457479 \tabularnewline
0.81 & 658.32123297112 & 10.0039843781106 \tabularnewline
0.82 & 660.3760805256 & 9.14979033290874 \tabularnewline
0.83 & 662.223300486173 & 7.98998282778411 \tabularnewline
0.84 & 663.809863520791 & 6.65034617535037 \tabularnewline
0.85 & 665.109480082622 & 5.26495387136512 \tabularnewline
0.86 & 666.122687013924 & 3.95563496041364 \tabularnewline
0.87 & 666.872666673911 & 2.81249205849886 \tabularnewline
0.88 & 667.398190894155 & 1.88606701235073 \tabularnewline
0.89 & 667.745535613929 & 1.18773185408457 \tabularnewline
0.9 & 667.961114510053 & 0.698760634912474 \tabularnewline
0.91 & 668.086050406933 & 0.381312584829681 \tabularnewline
0.92 & 668.153179861351 & 0.191454377082291 \tabularnewline
0.93 & 668.186318143938 & 0.0871069143491941 \tabularnewline
0.94 & 668.201170673004 & 0.035662453861663 \tabularnewline
0.95 & 668.207120300252 & 0.0126251867805593 \tabularnewline
0.96 & 668.209204652995 & 0.00381980130682075 \tabularnewline
0.97 & 668.209823381786 & 0.000954243807827248 \tabularnewline
0.98 & 668.209971362157 & 0.000191665076511808 \tabularnewline
0.99 & 668.209997345426 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153888&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]589.85025323665[/C][C]0.0013606870611333[/C][/ROW]
[ROW][C]0.02[/C][C]589.852104571938[/C][C]0.0102051529584997[/C][/ROW]
[ROW][C]0.03[/C][C]589.859966851168[/C][C]0.0425214706604156[/C][/ROW]
[ROW][C]0.04[/C][C]589.884348088057[/C][C]0.128755013159738[/C][/ROW]
[ROW][C]0.05[/C][C]589.944843270132[/C][C]0.310406735821034[/C][/ROW]
[ROW][C]0.06[/C][C]590.071015836292[/C][C]0.627616906947734[/C][/ROW]
[ROW][C]0.07[/C][C]590.29915109061[/C][C]1.09790437245193[/C][/ROW]
[ROW][C]0.08[/C][C]590.664394278517[/C][C]1.69929566666208[/C][/ROW]
[ROW][C]0.09[/C][C]591.190190509752[/C][C]2.36324621532467[/C][/ROW]
[ROW][C]0.1[/C][C]591.878833016419[/C][C]2.988944082518[/C][/ROW]
[ROW][C]0.11[/C][C]592.70706499834[/C][C]3.47045999535181[/C][/ROW]
[ROW][C]0.12[/C][C]593.628861280013[/C][C]3.72922355659422[/C][/ROW]
[ROW][C]0.13[/C][C]594.584691118784[/C][C]3.73358312288261[/C][/ROW]
[ROW][C]0.14[/C][C]595.514187334134[/C][C]3.50756509102746[/C][/ROW]
[ROW][C]0.15[/C][C]596.368276071228[/C][C]3.11832297381398[/C][/ROW]
[ROW][C]0.16[/C][C]597.117596077319[/C][C]2.6566621005116[/C][/ROW]
[ROW][C]0.17[/C][C]597.755789182589[/C][C]2.22079193994758[/C][/ROW]
[ROW][C]0.18[/C][C]598.29802598292[/C][C]1.90524269642378[/C][/ROW]
[ROW][C]0.19[/C][C]598.776246405299[/C][C]1.79681382209189[/C][/ROW]
[ROW][C]0.2[/C][C]599.232850361033[/C][C]1.94609160936344[/C][/ROW]
[ROW][C]0.21[/C][C]599.714203134328[/C][C]2.34448238807786[/C][/ROW]
[ROW][C]0.22[/C][C]600.264732549297[/C][C]2.94340139248091[/C][/ROW]
[ROW][C]0.23[/C][C]600.921929430793[/C][C]3.6852263835085[/C][/ROW]
[ROW][C]0.24[/C][C]601.71236347339[/C][C]4.50615110568799[/C][/ROW]
[ROW][C]0.25[/C][C]602.64884902461[/C][C]5.33355397709516[/C][/ROW]
[ROW][C]0.26[/C][C]603.728993397295[/C][C]6.09227204332232[/C][/ROW]
[ROW][C]0.27[/C][C]604.935387397574[/C][C]6.70960387353227[/C][/ROW]
[ROW][C]0.28[/C][C]606.237575919133[/C][C]7.12669781712311[/C][/ROW]
[ROW][C]0.29[/C][C]607.595687960634[/C][C]7.30676352259788[/C][/ROW]
[ROW][C]0.3[/C][C]608.96529195987[/C][C]7.23984560716225[/C][/ROW]
[ROW][C]0.31[/C][C]610.302781276548[/C][C]6.94542625648895[/C][/ROW]
[ROW][C]0.32[/C][C]611.570473570838[/C][C]6.46605171770647[/C][/ROW]
[ROW][C]0.33[/C][C]612.740664052042[/C][C]5.86414484180771[/C][/ROW]
[ROW][C]0.34[/C][C]613.798085825272[/C][C]5.21152735151977[/C][/ROW]
[ROW][C]0.35[/C][C]614.740537041865[/C][C]4.58033070486382[/C][/ROW]
[ROW][C]0.36[/C][C]615.577753578012[/C][C]4.03638529039765[/C][/ROW]
[ROW][C]0.37[/C][C]616.328867295157[/C][C]3.63398734909483[/C][/ROW]
[ROW][C]0.38[/C][C]617.018952010666[/C][C]3.4063500937085[/C][/ROW]
[ROW][C]0.39[/C][C]617.675213878795[/C][C]3.35816837238739[/C][/ROW]
[ROW][C]0.4[/C][C]618.323347698195[/C][C]3.46321301699705[/C][/ROW]
[ROW][C]0.41[/C][C]618.984485933625[/C][C]3.67407562188237[/C][/ROW]
[ROW][C]0.42[/C][C]619.673042606075[/C][C]3.93596077766668[/C][/ROW]
[ROW][C]0.43[/C][C]620.395620964271[/C][C]4.19612961805018[/C][/ROW]
[ROW][C]0.44[/C][C]621.15102377443[/C][C]4.41044930423598[/C][/ROW]
[ROW][C]0.45[/C][C]621.931283994314[/C][C]4.5448562602489[/C][/ROW]
[ROW][C]0.46[/C][C]622.72352638589[/C][C]4.57954594863739[/C][/ROW]
[ROW][C]0.47[/C][C]623.512384311069[/C][C]4.5088614846967[/C][/ROW]
[ROW][C]0.48[/C][C]624.282639705825[/C][C]4.34216514678512[/C][/ROW]
[ROW][C]0.49[/C][C]625.021736501251[/C][C]4.10208560737502[/C][/ROW]
[ROW][C]0.5[/C][C]625.721842651225[/C][C]3.8215403566818[/C][/ROW]
[ROW][C]0.51[/C][C]626.381200737954[/C][C]3.54159672745[/C][/ROW]
[ROW][C]0.52[/C][C]627.004602439014[/C][C]3.30619100299544[/C][/ROW]
[ROW][C]0.53[/C][C]627.602934256747[/C][C]3.157979702047[/C][/ROW]
[ROW][C]0.54[/C][C]628.191856396895[/C][C]3.12960555941353[/C][/ROW]
[ROW][C]0.55[/C][C]628.789781291612[/C][C]3.23486699844343[/C][/ROW]
[ROW][C]0.56[/C][C]629.415404064086[/C][C]3.46465027473067[/C][/ROW]
[ROW][C]0.57[/C][C]630.085097852564[/C][C]3.78852398695363[/C][/ROW]
[ROW][C]0.58[/C][C]630.810516887345[/C][C]4.16437046507824[/C][/ROW]
[ROW][C]0.59[/C][C]631.596744020706[/C][C]4.54471612120581[/C][/ROW]
[ROW][C]0.6[/C][C]632.441272329253[/C][C]4.88098312734033[/C][/ROW]
[ROW][C]0.61[/C][C]633.334021293879[/C][C]5.13022952748658[/C][/ROW]
[ROW][C]0.62[/C][C]634.258462728474[/C][C]5.26076346898231[/C][/ROW]
[ROW][C]0.63[/C][C]635.193784786331[/C][C]5.25391066750801[/C][/ROW]
[ROW][C]0.64[/C][C]636.117876266332[/C][C]5.10842240839949[/C][/ROW]
[ROW][C]0.65[/C][C]637.010792689152[/C][C]4.8429090430481[/C][/ROW]
[ROW][C]0.66[/C][C]637.858289747331[/C][C]4.49316588946641[/C][/ROW]
[ROW][C]0.67[/C][C]638.654986578631[/C][C]4.11199502250418[/C][/ROW]
[ROW][C]0.68[/C][C]639.406744793333[/C][C]3.76575947928778[/C][/ROW]
[ROW][C]0.69[/C][C]640.131903707713[/C][C]3.53385472773597[/C][/ROW]
[ROW][C]0.7[/C][C]640.86108281825[/C][C]3.50049322221392[/C][/ROW]
[ROW][C]0.71[/C][C]641.635346392154[/C][C]3.73369890292411[/C][/ROW]
[ROW][C]0.72[/C][C]642.502637880254[/C][C]4.25950541146783[/C][/ROW]
[ROW][C]0.73[/C][C]643.512562998867[/C][C]5.05443117188909[/C][/ROW]
[ROW][C]0.74[/C][C]644.709854571292[/C][C]6.05755339430143[/C][/ROW]
[ROW][C]0.75[/C][C]646.127183708154[/C][C]7.17868721433153[/C][/ROW]
[ROW][C]0.76[/C][C]647.778332275318[/C][C]8.30619494591645[/C][/ROW]
[ROW][C]0.77[/C][C]649.652997738982[/C][C]9.31363010159972[/C][/ROW]
[ROW][C]0.78[/C][C]651.714523630759[/C][C]10.0733652379867[/C][/ROW]
[ROW][C]0.79[/C][C]653.901526818739[/C][C]10.4789062057666[/C][/ROW]
[ROW][C]0.8[/C][C]656.133710782371[/C][C]10.460989457479[/C][/ROW]
[ROW][C]0.81[/C][C]658.32123297112[/C][C]10.0039843781106[/C][/ROW]
[ROW][C]0.82[/C][C]660.3760805256[/C][C]9.14979033290874[/C][/ROW]
[ROW][C]0.83[/C][C]662.223300486173[/C][C]7.98998282778411[/C][/ROW]
[ROW][C]0.84[/C][C]663.809863520791[/C][C]6.65034617535037[/C][/ROW]
[ROW][C]0.85[/C][C]665.109480082622[/C][C]5.26495387136512[/C][/ROW]
[ROW][C]0.86[/C][C]666.122687013924[/C][C]3.95563496041364[/C][/ROW]
[ROW][C]0.87[/C][C]666.872666673911[/C][C]2.81249205849886[/C][/ROW]
[ROW][C]0.88[/C][C]667.398190894155[/C][C]1.88606701235073[/C][/ROW]
[ROW][C]0.89[/C][C]667.745535613929[/C][C]1.18773185408457[/C][/ROW]
[ROW][C]0.9[/C][C]667.961114510053[/C][C]0.698760634912474[/C][/ROW]
[ROW][C]0.91[/C][C]668.086050406933[/C][C]0.381312584829681[/C][/ROW]
[ROW][C]0.92[/C][C]668.153179861351[/C][C]0.191454377082291[/C][/ROW]
[ROW][C]0.93[/C][C]668.186318143938[/C][C]0.0871069143491941[/C][/ROW]
[ROW][C]0.94[/C][C]668.201170673004[/C][C]0.035662453861663[/C][/ROW]
[ROW][C]0.95[/C][C]668.207120300252[/C][C]0.0126251867805593[/C][/ROW]
[ROW][C]0.96[/C][C]668.209204652995[/C][C]0.00381980130682075[/C][/ROW]
[ROW][C]0.97[/C][C]668.209823381786[/C][C]0.000954243807827248[/C][/ROW]
[ROW][C]0.98[/C][C]668.209971362157[/C][C]0.000191665076511808[/C][/ROW]
[ROW][C]0.99[/C][C]668.209997345426[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153888&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153888&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
0.01589.850253236650.0013606870611333
0.02589.8521045719380.0102051529584997
0.03589.8599668511680.0425214706604156
0.04589.8843480880570.128755013159738
0.05589.9448432701320.310406735821034
0.06590.0710158362920.627616906947734
0.07590.299151090611.09790437245193
0.08590.6643942785171.69929566666208
0.09591.1901905097522.36324621532467
0.1591.8788330164192.988944082518
0.11592.707064998343.47045999535181
0.12593.6288612800133.72922355659422
0.13594.5846911187843.73358312288261
0.14595.5141873341343.50756509102746
0.15596.3682760712283.11832297381398
0.16597.1175960773192.6566621005116
0.17597.7557891825892.22079193994758
0.18598.298025982921.90524269642378
0.19598.7762464052991.79681382209189
0.2599.2328503610331.94609160936344
0.21599.7142031343282.34448238807786
0.22600.2647325492972.94340139248091
0.23600.9219294307933.6852263835085
0.24601.712363473394.50615110568799
0.25602.648849024615.33355397709516
0.26603.7289933972956.09227204332232
0.27604.9353873975746.70960387353227
0.28606.2375759191337.12669781712311
0.29607.5956879606347.30676352259788
0.3608.965291959877.23984560716225
0.31610.3027812765486.94542625648895
0.32611.5704735708386.46605171770647
0.33612.7406640520425.86414484180771
0.34613.7980858252725.21152735151977
0.35614.7405370418654.58033070486382
0.36615.5777535780124.03638529039765
0.37616.3288672951573.63398734909483
0.38617.0189520106663.4063500937085
0.39617.6752138787953.35816837238739
0.4618.3233476981953.46321301699705
0.41618.9844859336253.67407562188237
0.42619.6730426060753.93596077766668
0.43620.3956209642714.19612961805018
0.44621.151023774434.41044930423598
0.45621.9312839943144.5448562602489
0.46622.723526385894.57954594863739
0.47623.5123843110694.5088614846967
0.48624.2826397058254.34216514678512
0.49625.0217365012514.10208560737502
0.5625.7218426512253.8215403566818
0.51626.3812007379543.54159672745
0.52627.0046024390143.30619100299544
0.53627.6029342567473.157979702047
0.54628.1918563968953.12960555941353
0.55628.7897812916123.23486699844343
0.56629.4154040640863.46465027473067
0.57630.0850978525643.78852398695363
0.58630.8105168873454.16437046507824
0.59631.5967440207064.54471612120581
0.6632.4412723292534.88098312734033
0.61633.3340212938795.13022952748658
0.62634.2584627284745.26076346898231
0.63635.1937847863315.25391066750801
0.64636.1178762663325.10842240839949
0.65637.0107926891524.8429090430481
0.66637.8582897473314.49316588946641
0.67638.6549865786314.11199502250418
0.68639.4067447933333.76575947928778
0.69640.1319037077133.53385472773597
0.7640.861082818253.50049322221392
0.71641.6353463921543.73369890292411
0.72642.5026378802544.25950541146783
0.73643.5125629988675.05443117188909
0.74644.7098545712926.05755339430143
0.75646.1271837081547.17868721433153
0.76647.7783322753188.30619494591645
0.77649.6529977389829.31363010159972
0.78651.71452363075910.0733652379867
0.79653.90152681873910.4789062057666
0.8656.13371078237110.460989457479
0.81658.3212329711210.0039843781106
0.82660.37608052569.14979033290874
0.83662.2233004861737.98998282778411
0.84663.8098635207916.65034617535037
0.85665.1094800826225.26495387136512
0.86666.1226870139243.95563496041364
0.87666.8726666739112.81249205849886
0.88667.3981908941551.88606701235073
0.89667.7455356139291.18773185408457
0.9667.9611145100530.698760634912474
0.91668.0860504069330.381312584829681
0.92668.1531798613510.191454377082291
0.93668.1863181439380.0871069143491941
0.94668.2011706730040.035662453861663
0.95668.2071203002520.0126251867805593
0.96668.2092046529950.00381980130682075
0.97668.2098233817860.000954243807827248
0.98668.2099713621570.000191665076511808
0.99668.2099973454260


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')