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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 computationTue, 17 Aug 2010 16:29:53 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Aug/17/t1282062556l3uheprwoms22vw.htm/, Retrieved Sat, 27 Apr 2024 06:37:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=79151, Retrieved Sat, 27 Apr 2024 06:37:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsmattias debbaut
Estimated Impact113

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 per...] [2010-08-17 16:29:53] [59fa324537f53fb6459bc6951db20f7b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
900
899
898
896
916
915
900
890
891
891
892
894
896
889
878
883
901
897
881
866
867
866
862
871
865
856
847
859
870
872
856
839
829
825
822
827
822
812
810
816
820
823
810
793
777
772
765
765
753
742
736
740
742
742
728
707
699
696
689
692
673
653
642
648
654
653
630
609
598
601
592
591
568
538
523
530
529
534
513
491
480
478
462
461
437
411
400
405
395
407
385
366
349
343
332
327
306
276
269
268
260
274
247
226
212
199
188
179
155
124
117
116
105
112
86
64
53
42
32
24

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79151&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79151&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79151&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Harrell-Davis Quantiles
quantilesvaluestandard error
0.0130.821042219636210.6205268802633
0.0242.698283662090216.6048354774083
0.0356.985375231387922.5106937209163
0.0472.48439138976526.1634175478856
0.0587.99318569569327.1890480687049
0.06102.75250751022327.6532115587516
0.07116.93053319494529.9493753479878
0.08131.28930275316634.3305329557223
0.09146.47787045477639.2164475641857
0.1162.60930874552443.0174398370985
0.11179.31233600972845.0620016038695
0.12196.03307651305745.5291706372509
0.13212.30760457160644.995968286448
0.14227.88628994435244.0804215698398
0.15242.73519472224643.3071453038752
0.16256.97947514458843.0670805393894
0.17270.82975941008743.5440872334519
0.18284.50760484996344.6498098457762
0.19298.18178407933246.0668642730873
0.2311.93016469386547.4070440916598
0.21325.73707532066248.3689951385715
0.22339.52278329333148.8362018990962
0.23353.18936964803748.8805585533604
0.24366.66343692770648.7051400310289
0.25379.92113190128648.551516557373
0.26392.99038683025948.6167882692275
0.27405.93416453922248.9854828829875
0.28418.82401791152949.6125797045171
0.29431.71470424560750.3543344645492
0.3444.62840488392651.0327833954706
0.31457.5524861903151.5091489022828
0.32470.44942901506351.7169820633398
0.33483.27342684184351.6832070449081
0.34495.98656067312151.4955245197827
0.35508.56867998940351.2641690839268
0.36521.01831699209951.0691129749084
0.37533.34565954834850.937440251309
0.38545.56137240477450.8299393273989
0.39557.66603283735350.6633309448761
0.4569.64407540621450.3466834707383
0.41581.4640342700649.8102445206929
0.42593.08447575320849.0260705234655
0.43604.46319988294748.0257542908971
0.44615.566550395346.8740444256583
0.45626.3760288456345.6581857050595
0.46636.89052518342844.46547433348
0.47647.1238873208743.3608677983384
0.48657.09884838685942.364309779538
0.49666.8392462534741.4662448169741
0.5676.36286501272140.6171442514963
0.51685.67704478242639.7540348523472
0.52694.77845900921738.8262760688317
0.53703.65726325172537.8087854515634
0.54712.30442724993136.7205993133004
0.55720.71984924933535.6240790012927
0.56728.91823925961134.6064157834819
0.57736.93007026625733.7555237993592
0.58744.79620457898233.1174455059920
0.59752.556827735832.6738737861187
0.6760.23746345794832.3274043957025
0.61767.83634886802231.9256526070047
0.62775.31768743606231.2939009798494
0.63782.6140156482430.2955477885897
0.64789.63838398286228.8622102882676
0.65796.30399534453727.0339440360941
0.66802.54633328401624.9481595410235
0.67808.34153264935422.8171327270421
0.68813.7153033215620.8815141102474
0.69818.739072639719.3460619232935
0.7823.51357238734518.3216063557860
0.71828.1438661875917.7795321002869
0.72832.71264836431617.5615514430175
0.73837.2595721499617.4312408861942
0.74841.77291174679817.1532570707024
0.75846.1963057864216.5597823084451
0.76850.44871829450415.5960927662384
0.77854.45160814874814.3216401139514
0.78858.15503986284512.8967132730847
0.79861.5548296192111.5240338515902
0.8864.69557018115610.3991175627666
0.81867.6585277132239.64956825917391
0.82870.5377310436329.28217319881747
0.83873.4110816095759.18528122064049
0.84876.3152999125029.16260833985422
0.85879.2333413545899.00853364671427
0.86882.0998560775618.57706761665969
0.87884.8241360893467.83045808684252
0.88887.3222749960686.84477640695277
0.89889.5448004239345.77561752235492
0.9891.4874224734474.78249123282134
0.91893.1819250713573.96068564658258
0.92894.6760412932933.31500445090426
0.93896.0170872324982.80301326765939
0.94897.255956676742.39123016709809
0.95898.5044739468852.13180828355417
0.96900.1025797144552.42430254441925
0.97902.8139067948594.14995630885075
0.98907.4063544466956.73395815403734
0.99912.9078459792645.92471774259608

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.01 & 30.8210422196362 & 10.6205268802633 \tabularnewline
0.02 & 42.6982836620902 & 16.6048354774083 \tabularnewline
0.03 & 56.9853752313879 & 22.5106937209163 \tabularnewline
0.04 & 72.484391389765 & 26.1634175478856 \tabularnewline
0.05 & 87.993185695693 & 27.1890480687049 \tabularnewline
0.06 & 102.752507510223 & 27.6532115587516 \tabularnewline
0.07 & 116.930533194945 & 29.9493753479878 \tabularnewline
0.08 & 131.289302753166 & 34.3305329557223 \tabularnewline
0.09 & 146.477870454776 & 39.2164475641857 \tabularnewline
0.1 & 162.609308745524 & 43.0174398370985 \tabularnewline
0.11 & 179.312336009728 & 45.0620016038695 \tabularnewline
0.12 & 196.033076513057 & 45.5291706372509 \tabularnewline
0.13 & 212.307604571606 & 44.995968286448 \tabularnewline
0.14 & 227.886289944352 & 44.0804215698398 \tabularnewline
0.15 & 242.735194722246 & 43.3071453038752 \tabularnewline
0.16 & 256.979475144588 & 43.0670805393894 \tabularnewline
0.17 & 270.829759410087 & 43.5440872334519 \tabularnewline
0.18 & 284.507604849963 & 44.6498098457762 \tabularnewline
0.19 & 298.181784079332 & 46.0668642730873 \tabularnewline
0.2 & 311.930164693865 & 47.4070440916598 \tabularnewline
0.21 & 325.737075320662 & 48.3689951385715 \tabularnewline
0.22 & 339.522783293331 & 48.8362018990962 \tabularnewline
0.23 & 353.189369648037 & 48.8805585533604 \tabularnewline
0.24 & 366.663436927706 & 48.7051400310289 \tabularnewline
0.25 & 379.921131901286 & 48.551516557373 \tabularnewline
0.26 & 392.990386830259 & 48.6167882692275 \tabularnewline
0.27 & 405.934164539222 & 48.9854828829875 \tabularnewline
0.28 & 418.824017911529 & 49.6125797045171 \tabularnewline
0.29 & 431.714704245607 & 50.3543344645492 \tabularnewline
0.3 & 444.628404883926 & 51.0327833954706 \tabularnewline
0.31 & 457.55248619031 & 51.5091489022828 \tabularnewline
0.32 & 470.449429015063 & 51.7169820633398 \tabularnewline
0.33 & 483.273426841843 & 51.6832070449081 \tabularnewline
0.34 & 495.986560673121 & 51.4955245197827 \tabularnewline
0.35 & 508.568679989403 & 51.2641690839268 \tabularnewline
0.36 & 521.018316992099 & 51.0691129749084 \tabularnewline
0.37 & 533.345659548348 & 50.937440251309 \tabularnewline
0.38 & 545.561372404774 & 50.8299393273989 \tabularnewline
0.39 & 557.666032837353 & 50.6633309448761 \tabularnewline
0.4 & 569.644075406214 & 50.3466834707383 \tabularnewline
0.41 & 581.46403427006 & 49.8102445206929 \tabularnewline
0.42 & 593.084475753208 & 49.0260705234655 \tabularnewline
0.43 & 604.463199882947 & 48.0257542908971 \tabularnewline
0.44 & 615.5665503953 & 46.8740444256583 \tabularnewline
0.45 & 626.37602884563 & 45.6581857050595 \tabularnewline
0.46 & 636.890525183428 & 44.46547433348 \tabularnewline
0.47 & 647.12388732087 & 43.3608677983384 \tabularnewline
0.48 & 657.098848386859 & 42.364309779538 \tabularnewline
0.49 & 666.83924625347 & 41.4662448169741 \tabularnewline
0.5 & 676.362865012721 & 40.6171442514963 \tabularnewline
0.51 & 685.677044782426 & 39.7540348523472 \tabularnewline
0.52 & 694.778459009217 & 38.8262760688317 \tabularnewline
0.53 & 703.657263251725 & 37.8087854515634 \tabularnewline
0.54 & 712.304427249931 & 36.7205993133004 \tabularnewline
0.55 & 720.719849249335 & 35.6240790012927 \tabularnewline
0.56 & 728.918239259611 & 34.6064157834819 \tabularnewline
0.57 & 736.930070266257 & 33.7555237993592 \tabularnewline
0.58 & 744.796204578982 & 33.1174455059920 \tabularnewline
0.59 & 752.5568277358 & 32.6738737861187 \tabularnewline
0.6 & 760.237463457948 & 32.3274043957025 \tabularnewline
0.61 & 767.836348868022 & 31.9256526070047 \tabularnewline
0.62 & 775.317687436062 & 31.2939009798494 \tabularnewline
0.63 & 782.61401564824 & 30.2955477885897 \tabularnewline
0.64 & 789.638383982862 & 28.8622102882676 \tabularnewline
0.65 & 796.303995344537 & 27.0339440360941 \tabularnewline
0.66 & 802.546333284016 & 24.9481595410235 \tabularnewline
0.67 & 808.341532649354 & 22.8171327270421 \tabularnewline
0.68 & 813.71530332156 & 20.8815141102474 \tabularnewline
0.69 & 818.7390726397 & 19.3460619232935 \tabularnewline
0.7 & 823.513572387345 & 18.3216063557860 \tabularnewline
0.71 & 828.14386618759 & 17.7795321002869 \tabularnewline
0.72 & 832.712648364316 & 17.5615514430175 \tabularnewline
0.73 & 837.25957214996 & 17.4312408861942 \tabularnewline
0.74 & 841.772911746798 & 17.1532570707024 \tabularnewline
0.75 & 846.19630578642 & 16.5597823084451 \tabularnewline
0.76 & 850.448718294504 & 15.5960927662384 \tabularnewline
0.77 & 854.451608148748 & 14.3216401139514 \tabularnewline
0.78 & 858.155039862845 & 12.8967132730847 \tabularnewline
0.79 & 861.55482961921 & 11.5240338515902 \tabularnewline
0.8 & 864.695570181156 & 10.3991175627666 \tabularnewline
0.81 & 867.658527713223 & 9.64956825917391 \tabularnewline
0.82 & 870.537731043632 & 9.28217319881747 \tabularnewline
0.83 & 873.411081609575 & 9.18528122064049 \tabularnewline
0.84 & 876.315299912502 & 9.16260833985422 \tabularnewline
0.85 & 879.233341354589 & 9.00853364671427 \tabularnewline
0.86 & 882.099856077561 & 8.57706761665969 \tabularnewline
0.87 & 884.824136089346 & 7.83045808684252 \tabularnewline
0.88 & 887.322274996068 & 6.84477640695277 \tabularnewline
0.89 & 889.544800423934 & 5.77561752235492 \tabularnewline
0.9 & 891.487422473447 & 4.78249123282134 \tabularnewline
0.91 & 893.181925071357 & 3.96068564658258 \tabularnewline
0.92 & 894.676041293293 & 3.31500445090426 \tabularnewline
0.93 & 896.017087232498 & 2.80301326765939 \tabularnewline
0.94 & 897.25595667674 & 2.39123016709809 \tabularnewline
0.95 & 898.504473946885 & 2.13180828355417 \tabularnewline
0.96 & 900.102579714455 & 2.42430254441925 \tabularnewline
0.97 & 902.813906794859 & 4.14995630885075 \tabularnewline
0.98 & 907.406354446695 & 6.73395815403734 \tabularnewline
0.99 & 912.907845979264 & 5.92471774259608 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79151&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]30.8210422196362[/C][C]10.6205268802633[/C][/ROW]
[ROW][C]0.02[/C][C]42.6982836620902[/C][C]16.6048354774083[/C][/ROW]
[ROW][C]0.03[/C][C]56.9853752313879[/C][C]22.5106937209163[/C][/ROW]
[ROW][C]0.04[/C][C]72.484391389765[/C][C]26.1634175478856[/C][/ROW]
[ROW][C]0.05[/C][C]87.993185695693[/C][C]27.1890480687049[/C][/ROW]
[ROW][C]0.06[/C][C]102.752507510223[/C][C]27.6532115587516[/C][/ROW]
[ROW][C]0.07[/C][C]116.930533194945[/C][C]29.9493753479878[/C][/ROW]
[ROW][C]0.08[/C][C]131.289302753166[/C][C]34.3305329557223[/C][/ROW]
[ROW][C]0.09[/C][C]146.477870454776[/C][C]39.2164475641857[/C][/ROW]
[ROW][C]0.1[/C][C]162.609308745524[/C][C]43.0174398370985[/C][/ROW]
[ROW][C]0.11[/C][C]179.312336009728[/C][C]45.0620016038695[/C][/ROW]
[ROW][C]0.12[/C][C]196.033076513057[/C][C]45.5291706372509[/C][/ROW]
[ROW][C]0.13[/C][C]212.307604571606[/C][C]44.995968286448[/C][/ROW]
[ROW][C]0.14[/C][C]227.886289944352[/C][C]44.0804215698398[/C][/ROW]
[ROW][C]0.15[/C][C]242.735194722246[/C][C]43.3071453038752[/C][/ROW]
[ROW][C]0.16[/C][C]256.979475144588[/C][C]43.0670805393894[/C][/ROW]
[ROW][C]0.17[/C][C]270.829759410087[/C][C]43.5440872334519[/C][/ROW]
[ROW][C]0.18[/C][C]284.507604849963[/C][C]44.6498098457762[/C][/ROW]
[ROW][C]0.19[/C][C]298.181784079332[/C][C]46.0668642730873[/C][/ROW]
[ROW][C]0.2[/C][C]311.930164693865[/C][C]47.4070440916598[/C][/ROW]
[ROW][C]0.21[/C][C]325.737075320662[/C][C]48.3689951385715[/C][/ROW]
[ROW][C]0.22[/C][C]339.522783293331[/C][C]48.8362018990962[/C][/ROW]
[ROW][C]0.23[/C][C]353.189369648037[/C][C]48.8805585533604[/C][/ROW]
[ROW][C]0.24[/C][C]366.663436927706[/C][C]48.7051400310289[/C][/ROW]
[ROW][C]0.25[/C][C]379.921131901286[/C][C]48.551516557373[/C][/ROW]
[ROW][C]0.26[/C][C]392.990386830259[/C][C]48.6167882692275[/C][/ROW]
[ROW][C]0.27[/C][C]405.934164539222[/C][C]48.9854828829875[/C][/ROW]
[ROW][C]0.28[/C][C]418.824017911529[/C][C]49.6125797045171[/C][/ROW]
[ROW][C]0.29[/C][C]431.714704245607[/C][C]50.3543344645492[/C][/ROW]
[ROW][C]0.3[/C][C]444.628404883926[/C][C]51.0327833954706[/C][/ROW]
[ROW][C]0.31[/C][C]457.55248619031[/C][C]51.5091489022828[/C][/ROW]
[ROW][C]0.32[/C][C]470.449429015063[/C][C]51.7169820633398[/C][/ROW]
[ROW][C]0.33[/C][C]483.273426841843[/C][C]51.6832070449081[/C][/ROW]
[ROW][C]0.34[/C][C]495.986560673121[/C][C]51.4955245197827[/C][/ROW]
[ROW][C]0.35[/C][C]508.568679989403[/C][C]51.2641690839268[/C][/ROW]
[ROW][C]0.36[/C][C]521.018316992099[/C][C]51.0691129749084[/C][/ROW]
[ROW][C]0.37[/C][C]533.345659548348[/C][C]50.937440251309[/C][/ROW]
[ROW][C]0.38[/C][C]545.561372404774[/C][C]50.8299393273989[/C][/ROW]
[ROW][C]0.39[/C][C]557.666032837353[/C][C]50.6633309448761[/C][/ROW]
[ROW][C]0.4[/C][C]569.644075406214[/C][C]50.3466834707383[/C][/ROW]
[ROW][C]0.41[/C][C]581.46403427006[/C][C]49.8102445206929[/C][/ROW]
[ROW][C]0.42[/C][C]593.084475753208[/C][C]49.0260705234655[/C][/ROW]
[ROW][C]0.43[/C][C]604.463199882947[/C][C]48.0257542908971[/C][/ROW]
[ROW][C]0.44[/C][C]615.5665503953[/C][C]46.8740444256583[/C][/ROW]
[ROW][C]0.45[/C][C]626.37602884563[/C][C]45.6581857050595[/C][/ROW]
[ROW][C]0.46[/C][C]636.890525183428[/C][C]44.46547433348[/C][/ROW]
[ROW][C]0.47[/C][C]647.12388732087[/C][C]43.3608677983384[/C][/ROW]
[ROW][C]0.48[/C][C]657.098848386859[/C][C]42.364309779538[/C][/ROW]
[ROW][C]0.49[/C][C]666.83924625347[/C][C]41.4662448169741[/C][/ROW]
[ROW][C]0.5[/C][C]676.362865012721[/C][C]40.6171442514963[/C][/ROW]
[ROW][C]0.51[/C][C]685.677044782426[/C][C]39.7540348523472[/C][/ROW]
[ROW][C]0.52[/C][C]694.778459009217[/C][C]38.8262760688317[/C][/ROW]
[ROW][C]0.53[/C][C]703.657263251725[/C][C]37.8087854515634[/C][/ROW]
[ROW][C]0.54[/C][C]712.304427249931[/C][C]36.7205993133004[/C][/ROW]
[ROW][C]0.55[/C][C]720.719849249335[/C][C]35.6240790012927[/C][/ROW]
[ROW][C]0.56[/C][C]728.918239259611[/C][C]34.6064157834819[/C][/ROW]
[ROW][C]0.57[/C][C]736.930070266257[/C][C]33.7555237993592[/C][/ROW]
[ROW][C]0.58[/C][C]744.796204578982[/C][C]33.1174455059920[/C][/ROW]
[ROW][C]0.59[/C][C]752.5568277358[/C][C]32.6738737861187[/C][/ROW]
[ROW][C]0.6[/C][C]760.237463457948[/C][C]32.3274043957025[/C][/ROW]
[ROW][C]0.61[/C][C]767.836348868022[/C][C]31.9256526070047[/C][/ROW]
[ROW][C]0.62[/C][C]775.317687436062[/C][C]31.2939009798494[/C][/ROW]
[ROW][C]0.63[/C][C]782.61401564824[/C][C]30.2955477885897[/C][/ROW]
[ROW][C]0.64[/C][C]789.638383982862[/C][C]28.8622102882676[/C][/ROW]
[ROW][C]0.65[/C][C]796.303995344537[/C][C]27.0339440360941[/C][/ROW]
[ROW][C]0.66[/C][C]802.546333284016[/C][C]24.9481595410235[/C][/ROW]
[ROW][C]0.67[/C][C]808.341532649354[/C][C]22.8171327270421[/C][/ROW]
[ROW][C]0.68[/C][C]813.71530332156[/C][C]20.8815141102474[/C][/ROW]
[ROW][C]0.69[/C][C]818.7390726397[/C][C]19.3460619232935[/C][/ROW]
[ROW][C]0.7[/C][C]823.513572387345[/C][C]18.3216063557860[/C][/ROW]
[ROW][C]0.71[/C][C]828.14386618759[/C][C]17.7795321002869[/C][/ROW]
[ROW][C]0.72[/C][C]832.712648364316[/C][C]17.5615514430175[/C][/ROW]
[ROW][C]0.73[/C][C]837.25957214996[/C][C]17.4312408861942[/C][/ROW]
[ROW][C]0.74[/C][C]841.772911746798[/C][C]17.1532570707024[/C][/ROW]
[ROW][C]0.75[/C][C]846.19630578642[/C][C]16.5597823084451[/C][/ROW]
[ROW][C]0.76[/C][C]850.448718294504[/C][C]15.5960927662384[/C][/ROW]
[ROW][C]0.77[/C][C]854.451608148748[/C][C]14.3216401139514[/C][/ROW]
[ROW][C]0.78[/C][C]858.155039862845[/C][C]12.8967132730847[/C][/ROW]
[ROW][C]0.79[/C][C]861.55482961921[/C][C]11.5240338515902[/C][/ROW]
[ROW][C]0.8[/C][C]864.695570181156[/C][C]10.3991175627666[/C][/ROW]
[ROW][C]0.81[/C][C]867.658527713223[/C][C]9.64956825917391[/C][/ROW]
[ROW][C]0.82[/C][C]870.537731043632[/C][C]9.28217319881747[/C][/ROW]
[ROW][C]0.83[/C][C]873.411081609575[/C][C]9.18528122064049[/C][/ROW]
[ROW][C]0.84[/C][C]876.315299912502[/C][C]9.16260833985422[/C][/ROW]
[ROW][C]0.85[/C][C]879.233341354589[/C][C]9.00853364671427[/C][/ROW]
[ROW][C]0.86[/C][C]882.099856077561[/C][C]8.57706761665969[/C][/ROW]
[ROW][C]0.87[/C][C]884.824136089346[/C][C]7.83045808684252[/C][/ROW]
[ROW][C]0.88[/C][C]887.322274996068[/C][C]6.84477640695277[/C][/ROW]
[ROW][C]0.89[/C][C]889.544800423934[/C][C]5.77561752235492[/C][/ROW]
[ROW][C]0.9[/C][C]891.487422473447[/C][C]4.78249123282134[/C][/ROW]
[ROW][C]0.91[/C][C]893.181925071357[/C][C]3.96068564658258[/C][/ROW]
[ROW][C]0.92[/C][C]894.676041293293[/C][C]3.31500445090426[/C][/ROW]
[ROW][C]0.93[/C][C]896.017087232498[/C][C]2.80301326765939[/C][/ROW]
[ROW][C]0.94[/C][C]897.25595667674[/C][C]2.39123016709809[/C][/ROW]
[ROW][C]0.95[/C][C]898.504473946885[/C][C]2.13180828355417[/C][/ROW]
[ROW][C]0.96[/C][C]900.102579714455[/C][C]2.42430254441925[/C][/ROW]
[ROW][C]0.97[/C][C]902.813906794859[/C][C]4.14995630885075[/C][/ROW]
[ROW][C]0.98[/C][C]907.406354446695[/C][C]6.73395815403734[/C][/ROW]
[ROW][C]0.99[/C][C]912.907845979264[/C][C]5.92471774259608[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79151&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79151&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
0.0130.821042219636210.6205268802633
0.0242.698283662090216.6048354774083
0.0356.985375231387922.5106937209163
0.0472.48439138976526.1634175478856
0.0587.99318569569327.1890480687049
0.06102.75250751022327.6532115587516
0.07116.93053319494529.9493753479878
0.08131.28930275316634.3305329557223
0.09146.47787045477639.2164475641857
0.1162.60930874552443.0174398370985
0.11179.31233600972845.0620016038695
0.12196.03307651305745.5291706372509
0.13212.30760457160644.995968286448
0.14227.88628994435244.0804215698398
0.15242.73519472224643.3071453038752
0.16256.97947514458843.0670805393894
0.17270.82975941008743.5440872334519
0.18284.50760484996344.6498098457762
0.19298.18178407933246.0668642730873
0.2311.93016469386547.4070440916598
0.21325.73707532066248.3689951385715
0.22339.52278329333148.8362018990962
0.23353.18936964803748.8805585533604
0.24366.66343692770648.7051400310289
0.25379.92113190128648.551516557373
0.26392.99038683025948.6167882692275
0.27405.93416453922248.9854828829875
0.28418.82401791152949.6125797045171
0.29431.71470424560750.3543344645492
0.3444.62840488392651.0327833954706
0.31457.5524861903151.5091489022828
0.32470.44942901506351.7169820633398
0.33483.27342684184351.6832070449081
0.34495.98656067312151.4955245197827
0.35508.56867998940351.2641690839268
0.36521.01831699209951.0691129749084
0.37533.34565954834850.937440251309
0.38545.56137240477450.8299393273989
0.39557.66603283735350.6633309448761
0.4569.64407540621450.3466834707383
0.41581.4640342700649.8102445206929
0.42593.08447575320849.0260705234655
0.43604.46319988294748.0257542908971
0.44615.566550395346.8740444256583
0.45626.3760288456345.6581857050595
0.46636.89052518342844.46547433348
0.47647.1238873208743.3608677983384
0.48657.09884838685942.364309779538
0.49666.8392462534741.4662448169741
0.5676.36286501272140.6171442514963
0.51685.67704478242639.7540348523472
0.52694.77845900921738.8262760688317
0.53703.65726325172537.8087854515634
0.54712.30442724993136.7205993133004
0.55720.71984924933535.6240790012927
0.56728.91823925961134.6064157834819
0.57736.93007026625733.7555237993592
0.58744.79620457898233.1174455059920
0.59752.556827735832.6738737861187
0.6760.23746345794832.3274043957025
0.61767.83634886802231.9256526070047
0.62775.31768743606231.2939009798494
0.63782.6140156482430.2955477885897
0.64789.63838398286228.8622102882676
0.65796.30399534453727.0339440360941
0.66802.54633328401624.9481595410235
0.67808.34153264935422.8171327270421
0.68813.7153033215620.8815141102474
0.69818.739072639719.3460619232935
0.7823.51357238734518.3216063557860
0.71828.1438661875917.7795321002869
0.72832.71264836431617.5615514430175
0.73837.2595721499617.4312408861942
0.74841.77291174679817.1532570707024
0.75846.1963057864216.5597823084451
0.76850.44871829450415.5960927662384
0.77854.45160814874814.3216401139514
0.78858.15503986284512.8967132730847
0.79861.5548296192111.5240338515902
0.8864.69557018115610.3991175627666
0.81867.6585277132239.64956825917391
0.82870.5377310436329.28217319881747
0.83873.4110816095759.18528122064049
0.84876.3152999125029.16260833985422
0.85879.2333413545899.00853364671427
0.86882.0998560775618.57706761665969
0.87884.8241360893467.83045808684252
0.88887.3222749960686.84477640695277
0.89889.5448004239345.77561752235492
0.9891.4874224734474.78249123282134
0.91893.1819250713573.96068564658258
0.92894.6760412932933.31500445090426
0.93896.0170872324982.80301326765939
0.94897.255956676742.39123016709809
0.95898.5044739468852.13180828355417
0.96900.1025797144552.42430254441925
0.97902.8139067948594.14995630885075
0.98907.4063544466956.73395815403734
0.99912.9078459792645.92471774259608


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')