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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_harrell_davis.wasp
Title produced by softwareHarrell-Davis Quantiles
Date of computationTue, 02 Nov 2010 15:26:48 +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/Nov/02/t1288711522zofh1e564elmbtw.htm/, Retrieved Sat, 27 Apr 2024 14:36:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=91684, Retrieved Sat, 27 Apr 2024 14:36:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124

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] [WS5: Deel 2 Vraag 1] [2010-10-30 13:21:51] [1fd136673b2a4fecb5c545b9b4a05d64]
-   P   [Harrell-Davis Quantiles] [ws5 part 2 q1] [2010-11-02 15:19:43] [c1a9f1d6a1a56eda57b5ddd6daa7a288]
-   P       [Harrell-Davis Quantiles] [ws5 part 2 q1] [2010-11-02 15:26:48] [350231caf55a86a218fd48dc4d2e2f8b] [Current]
-   P         [Harrell-Davis Quantiles] [ws5 part 2 q1] [2010-11-02 15:28:35] [c1a9f1d6a1a56eda57b5ddd6daa7a288]
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Dataset

Dataseries X:
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Histogram
Boxplots 
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4.3076653355456E-14
0.0038240964384433
3.9523939676656E-14
3.9523939676656E-14
3.9523939676656E-14
-0.0038240964383607
4.3076653355456E-14
4.3076653355456E-14
4.3076653355456E-14
4.3076653355456E-14
0.0038240964384433
-0.0038240964383607
4.3076653355456E-14
4.3076653355456E-14
4.3076653355456E-14
0.0038240964384433
0.0094967475372392
0.0062814276885823
-2.1316282072803E-14
-0.0062814276886214
-1.7763568394003E-14
-1.7763568394003E-14
-1.7763568394003E-14
0.0062814276885823
-2.1316282072803E-14
-2.1316282072803E-14
-0.0062814276886214
-1.7763568394003E-14

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 4 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91684&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91684&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91684&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 time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Harrell-Davis Quantiles
quantilesvaluestandard error
0.001-0.01389661461577870.000367573518046186
0.011-0.008183264683430570.000867978872809949
0.021-0.007161393688912430.000104258672558594
0.031-0.006981545507510180.000142378710696068
0.041-0.006745988156719650.000207954892221286
0.051-0.006414358583557620.000332483665325154
0.061-0.006031502031853150.000320499722917276
0.071-0.005708230381090360.000293168021502747
0.081-0.005384917081620760.000411800067253306
0.091-0.004808389224490490.00100312341398463
0.101-0.003597477161182530.00187509715756753
0.111-0.001957976475059440.00192645309911412
0.121-0.0007057145773367740.00107538701136083
0.131-0.0001614828822013070.000337062187387916
0.141-2.31984250601023e-056.13630461862344e-05
0.151-2.10086716285627e-066.68750442062184e-06
0.161-1.21247332650576e-074.48036338669822e-07
0.171-4.52043555240645e-091.8890359820965e-08
0.181-1.10487203289753e-105.11794343177028e-10
0.191-1.83896313561993e-129.07894201249133e-12
0.201-6.37693498231092e-141.08849140543908e-13
0.211-4.27562831407604e-143.15848815787168e-15
0.221-4.10220380021872e-142.54967089401847e-15
0.231-3.95149465485271e-142.3079799458643e-15
0.241-3.82022478209831e-142.01611346955311e-15
0.251-3.69817882131336e-142.14726041961129e-15
0.261-3.54911875812555e-143.08969753028979e-15
0.271-3.33176821822752e-144.56399231814795e-15
0.281-3.04003989071257e-145.63254725597742e-15
0.291-2.72001053808414e-145.54212909569742e-15
0.301-2.43605979001261e-144.45567056707476e-15
0.311-2.22290537319759e-143.15959337621131e-15
0.321-2.072426254491e-142.30649169517481e-15
0.331-1.9522339558008e-142.12829723213232e-15
0.341-1.82854477976511e-142.47834518231043e-15
0.351-1.68372425619243e-142.91943457511274e-15
0.361-1.52365040383128e-143.04537589748988e-15
0.371-1.36738982706708e-142.79930341890972e-15
0.381-1.22981728389661e-142.37874811940578e-15
0.391-1.11654044407228e-141.91276650262423e-15
0.401-1.02917803407426e-141.42300876305275e-15
0.411-9.66810037200523e-159.81988602577306e-16
0.421-9.23646068119357e-156.95886105061769e-16
0.431-8.90619151762771e-155.91975059571109e-16
0.441-8.5915460618854e-156.38619192265022e-16
0.451-8.2188104243122e-158.25111669671241e-16
0.461-7.71892214504633e-151.13979970287138e-15
0.471-7.02952615624256e-151.56974758969107e-15
0.481-6.06711236689348e-152.22572670294611e-15
0.491-4.65634945831946e-153.35683422962229e-15
0.501-2.53562143244171e-155.00359715069001e-15
0.5114.40759853389716e-166.62793767890865e-15
0.5214.03736355546896e-157.33389865931624e-15
0.5317.63941257226886e-156.64378987346235e-15
0.5411.06186284045737e-144.99165075011006e-15
0.5511.27328500928277e-143.34424620587678e-15
0.5611.41929988284322e-142.42890212966976e-15
0.5711.54139541840457e-142.3506794232542e-15
0.5811.67364973415372e-142.76158042130323e-15
0.5911.83128873630605e-143.27740975886432e-15
0.6012.01334839154135e-143.65538822601214e-15
0.6112.20910648800516e-143.76679398756444e-15
0.6212.40300590522192e-143.55983557768553e-15
0.6312.57832900814734e-143.05048009137407e-15
0.6412.72073049194018e-142.32112171831493e-15
0.6512.82221577439267e-141.52740951921935e-15
0.6612.88471307198414e-148.69548428308428e-16
0.6712.92062049253009e-145.19739095164953e-16
0.6812.94956906122346e-145.81395166979416e-16
0.6912.9926437881005e-141.00123194916502e-15
0.7013.06333208968873e-141.52493926600296e-15
0.7113.157897435446e-141.80374080154156e-15
0.7213.27113441897778e-142.39909210648357e-15
0.7314.40649459008942e-146.28560516523661e-14
0.7415.98386038566594e-133.04823537581402e-12
0.7512.20131288029649e-111.09465449934681e-10
0.7616.26513798649962e-102.84970572451632e-09
0.7711.30038356406424e-085.33848223179988e-08
0.7811.95551993380109e-077.13855116464639e-07
0.7912.11969682847511e-066.75086419204585e-06
0.8011.64873174385999e-054.46819189586174e-05
0.8119.17581606139275e-050.00020461475678841
0.8210.0003656052608001410.000640435375114125
0.8310.001050273663617690.00135329260197506
0.8410.002214949668350120.00190880712769662
0.8510.003553270918748180.00178614265259263
0.8610.00459924366061550.00113227906163434
0.8710.005196877612430990.000563259961054099
0.8810.00552471155109810.000334524812094888
0.8910.005774299017080170.000291535374540362
0.9010.006033116656279670.000316217297831294
0.9110.006333638344850010.000347637636964456
0.9210.006637379762620030.000295777459384629
0.9310.006881377377729750.000209065607322487
0.9410.007098659887616330.000216773425977669
0.9510.007580506856447430.000632431823998246
0.9610.008970571144265320.00141486711553062
0.9710.01169404734742180.00212194631990681
0.9810.01697205965835970.00387446213985401

\begin{tabular}{lllllllll}
\hline
Harrell-Davis Quantiles \tabularnewline
quantiles & value & standard error \tabularnewline
0.001 & -0.0138966146157787 & 0.000367573518046186 \tabularnewline
0.011 & -0.00818326468343057 & 0.000867978872809949 \tabularnewline
0.021 & -0.00716139368891243 & 0.000104258672558594 \tabularnewline
0.031 & -0.00698154550751018 & 0.000142378710696068 \tabularnewline
0.041 & -0.00674598815671965 & 0.000207954892221286 \tabularnewline
0.051 & -0.00641435858355762 & 0.000332483665325154 \tabularnewline
0.061 & -0.00603150203185315 & 0.000320499722917276 \tabularnewline
0.071 & -0.00570823038109036 & 0.000293168021502747 \tabularnewline
0.081 & -0.00538491708162076 & 0.000411800067253306 \tabularnewline
0.091 & -0.00480838922449049 & 0.00100312341398463 \tabularnewline
0.101 & -0.00359747716118253 & 0.00187509715756753 \tabularnewline
0.111 & -0.00195797647505944 & 0.00192645309911412 \tabularnewline
0.121 & -0.000705714577336774 & 0.00107538701136083 \tabularnewline
0.131 & -0.000161482882201307 & 0.000337062187387916 \tabularnewline
0.141 & -2.31984250601023e-05 & 6.13630461862344e-05 \tabularnewline
0.151 & -2.10086716285627e-06 & 6.68750442062184e-06 \tabularnewline
0.161 & -1.21247332650576e-07 & 4.48036338669822e-07 \tabularnewline
0.171 & -4.52043555240645e-09 & 1.8890359820965e-08 \tabularnewline
0.181 & -1.10487203289753e-10 & 5.11794343177028e-10 \tabularnewline
0.191 & -1.83896313561993e-12 & 9.07894201249133e-12 \tabularnewline
0.201 & -6.37693498231092e-14 & 1.08849140543908e-13 \tabularnewline
0.211 & -4.27562831407604e-14 & 3.15848815787168e-15 \tabularnewline
0.221 & -4.10220380021872e-14 & 2.54967089401847e-15 \tabularnewline
0.231 & -3.95149465485271e-14 & 2.3079799458643e-15 \tabularnewline
0.241 & -3.82022478209831e-14 & 2.01611346955311e-15 \tabularnewline
0.251 & -3.69817882131336e-14 & 2.14726041961129e-15 \tabularnewline
0.261 & -3.54911875812555e-14 & 3.08969753028979e-15 \tabularnewline
0.271 & -3.33176821822752e-14 & 4.56399231814795e-15 \tabularnewline
0.281 & -3.04003989071257e-14 & 5.63254725597742e-15 \tabularnewline
0.291 & -2.72001053808414e-14 & 5.54212909569742e-15 \tabularnewline
0.301 & -2.43605979001261e-14 & 4.45567056707476e-15 \tabularnewline
0.311 & -2.22290537319759e-14 & 3.15959337621131e-15 \tabularnewline
0.321 & -2.072426254491e-14 & 2.30649169517481e-15 \tabularnewline
0.331 & -1.9522339558008e-14 & 2.12829723213232e-15 \tabularnewline
0.341 & -1.82854477976511e-14 & 2.47834518231043e-15 \tabularnewline
0.351 & -1.68372425619243e-14 & 2.91943457511274e-15 \tabularnewline
0.361 & -1.52365040383128e-14 & 3.04537589748988e-15 \tabularnewline
0.371 & -1.36738982706708e-14 & 2.79930341890972e-15 \tabularnewline
0.381 & -1.22981728389661e-14 & 2.37874811940578e-15 \tabularnewline
0.391 & -1.11654044407228e-14 & 1.91276650262423e-15 \tabularnewline
0.401 & -1.02917803407426e-14 & 1.42300876305275e-15 \tabularnewline
0.411 & -9.66810037200523e-15 & 9.81988602577306e-16 \tabularnewline
0.421 & -9.23646068119357e-15 & 6.95886105061769e-16 \tabularnewline
0.431 & -8.90619151762771e-15 & 5.91975059571109e-16 \tabularnewline
0.441 & -8.5915460618854e-15 & 6.38619192265022e-16 \tabularnewline
0.451 & -8.2188104243122e-15 & 8.25111669671241e-16 \tabularnewline
0.461 & -7.71892214504633e-15 & 1.13979970287138e-15 \tabularnewline
0.471 & -7.02952615624256e-15 & 1.56974758969107e-15 \tabularnewline
0.481 & -6.06711236689348e-15 & 2.22572670294611e-15 \tabularnewline
0.491 & -4.65634945831946e-15 & 3.35683422962229e-15 \tabularnewline
0.501 & -2.53562143244171e-15 & 5.00359715069001e-15 \tabularnewline
0.511 & 4.40759853389716e-16 & 6.62793767890865e-15 \tabularnewline
0.521 & 4.03736355546896e-15 & 7.33389865931624e-15 \tabularnewline
0.531 & 7.63941257226886e-15 & 6.64378987346235e-15 \tabularnewline
0.541 & 1.06186284045737e-14 & 4.99165075011006e-15 \tabularnewline
0.551 & 1.27328500928277e-14 & 3.34424620587678e-15 \tabularnewline
0.561 & 1.41929988284322e-14 & 2.42890212966976e-15 \tabularnewline
0.571 & 1.54139541840457e-14 & 2.3506794232542e-15 \tabularnewline
0.581 & 1.67364973415372e-14 & 2.76158042130323e-15 \tabularnewline
0.591 & 1.83128873630605e-14 & 3.27740975886432e-15 \tabularnewline
0.601 & 2.01334839154135e-14 & 3.65538822601214e-15 \tabularnewline
0.611 & 2.20910648800516e-14 & 3.76679398756444e-15 \tabularnewline
0.621 & 2.40300590522192e-14 & 3.55983557768553e-15 \tabularnewline
0.631 & 2.57832900814734e-14 & 3.05048009137407e-15 \tabularnewline
0.641 & 2.72073049194018e-14 & 2.32112171831493e-15 \tabularnewline
0.651 & 2.82221577439267e-14 & 1.52740951921935e-15 \tabularnewline
0.661 & 2.88471307198414e-14 & 8.69548428308428e-16 \tabularnewline
0.671 & 2.92062049253009e-14 & 5.19739095164953e-16 \tabularnewline
0.681 & 2.94956906122346e-14 & 5.81395166979416e-16 \tabularnewline
0.691 & 2.9926437881005e-14 & 1.00123194916502e-15 \tabularnewline
0.701 & 3.06333208968873e-14 & 1.52493926600296e-15 \tabularnewline
0.711 & 3.157897435446e-14 & 1.80374080154156e-15 \tabularnewline
0.721 & 3.27113441897778e-14 & 2.39909210648357e-15 \tabularnewline
0.731 & 4.40649459008942e-14 & 6.28560516523661e-14 \tabularnewline
0.741 & 5.98386038566594e-13 & 3.04823537581402e-12 \tabularnewline
0.751 & 2.20131288029649e-11 & 1.09465449934681e-10 \tabularnewline
0.761 & 6.26513798649962e-10 & 2.84970572451632e-09 \tabularnewline
0.771 & 1.30038356406424e-08 & 5.33848223179988e-08 \tabularnewline
0.781 & 1.95551993380109e-07 & 7.13855116464639e-07 \tabularnewline
0.791 & 2.11969682847511e-06 & 6.75086419204585e-06 \tabularnewline
0.801 & 1.64873174385999e-05 & 4.46819189586174e-05 \tabularnewline
0.811 & 9.17581606139275e-05 & 0.00020461475678841 \tabularnewline
0.821 & 0.000365605260800141 & 0.000640435375114125 \tabularnewline
0.831 & 0.00105027366361769 & 0.00135329260197506 \tabularnewline
0.841 & 0.00221494966835012 & 0.00190880712769662 \tabularnewline
0.851 & 0.00355327091874818 & 0.00178614265259263 \tabularnewline
0.861 & 0.0045992436606155 & 0.00113227906163434 \tabularnewline
0.871 & 0.00519687761243099 & 0.000563259961054099 \tabularnewline
0.881 & 0.0055247115510981 & 0.000334524812094888 \tabularnewline
0.891 & 0.00577429901708017 & 0.000291535374540362 \tabularnewline
0.901 & 0.00603311665627967 & 0.000316217297831294 \tabularnewline
0.911 & 0.00633363834485001 & 0.000347637636964456 \tabularnewline
0.921 & 0.00663737976262003 & 0.000295777459384629 \tabularnewline
0.931 & 0.00688137737772975 & 0.000209065607322487 \tabularnewline
0.941 & 0.00709865988761633 & 0.000216773425977669 \tabularnewline
0.951 & 0.00758050685644743 & 0.000632431823998246 \tabularnewline
0.961 & 0.00897057114426532 & 0.00141486711553062 \tabularnewline
0.971 & 0.0116940473474218 & 0.00212194631990681 \tabularnewline
0.981 & 0.0169720596583597 & 0.00387446213985401 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=91684&T=1

[TABLE]
[ROW][C]Harrell-Davis Quantiles[/C][/ROW]
[ROW][C]quantiles[/C][C]value[/C][C]standard error[/C][/ROW]
[ROW][C]0.001[/C][C]-0.0138966146157787[/C][C]0.000367573518046186[/C][/ROW]
[ROW][C]0.011[/C][C]-0.00818326468343057[/C][C]0.000867978872809949[/C][/ROW]
[ROW][C]0.021[/C][C]-0.00716139368891243[/C][C]0.000104258672558594[/C][/ROW]
[ROW][C]0.031[/C][C]-0.00698154550751018[/C][C]0.000142378710696068[/C][/ROW]
[ROW][C]0.041[/C][C]-0.00674598815671965[/C][C]0.000207954892221286[/C][/ROW]
[ROW][C]0.051[/C][C]-0.00641435858355762[/C][C]0.000332483665325154[/C][/ROW]
[ROW][C]0.061[/C][C]-0.00603150203185315[/C][C]0.000320499722917276[/C][/ROW]
[ROW][C]0.071[/C][C]-0.00570823038109036[/C][C]0.000293168021502747[/C][/ROW]
[ROW][C]0.081[/C][C]-0.00538491708162076[/C][C]0.000411800067253306[/C][/ROW]
[ROW][C]0.091[/C][C]-0.00480838922449049[/C][C]0.00100312341398463[/C][/ROW]
[ROW][C]0.101[/C][C]-0.00359747716118253[/C][C]0.00187509715756753[/C][/ROW]
[ROW][C]0.111[/C][C]-0.00195797647505944[/C][C]0.00192645309911412[/C][/ROW]
[ROW][C]0.121[/C][C]-0.000705714577336774[/C][C]0.00107538701136083[/C][/ROW]
[ROW][C]0.131[/C][C]-0.000161482882201307[/C][C]0.000337062187387916[/C][/ROW]
[ROW][C]0.141[/C][C]-2.31984250601023e-05[/C][C]6.13630461862344e-05[/C][/ROW]
[ROW][C]0.151[/C][C]-2.10086716285627e-06[/C][C]6.68750442062184e-06[/C][/ROW]
[ROW][C]0.161[/C][C]-1.21247332650576e-07[/C][C]4.48036338669822e-07[/C][/ROW]
[ROW][C]0.171[/C][C]-4.52043555240645e-09[/C][C]1.8890359820965e-08[/C][/ROW]
[ROW][C]0.181[/C][C]-1.10487203289753e-10[/C][C]5.11794343177028e-10[/C][/ROW]
[ROW][C]0.191[/C][C]-1.83896313561993e-12[/C][C]9.07894201249133e-12[/C][/ROW]
[ROW][C]0.201[/C][C]-6.37693498231092e-14[/C][C]1.08849140543908e-13[/C][/ROW]
[ROW][C]0.211[/C][C]-4.27562831407604e-14[/C][C]3.15848815787168e-15[/C][/ROW]
[ROW][C]0.221[/C][C]-4.10220380021872e-14[/C][C]2.54967089401847e-15[/C][/ROW]
[ROW][C]0.231[/C][C]-3.95149465485271e-14[/C][C]2.3079799458643e-15[/C][/ROW]
[ROW][C]0.241[/C][C]-3.82022478209831e-14[/C][C]2.01611346955311e-15[/C][/ROW]
[ROW][C]0.251[/C][C]-3.69817882131336e-14[/C][C]2.14726041961129e-15[/C][/ROW]
[ROW][C]0.261[/C][C]-3.54911875812555e-14[/C][C]3.08969753028979e-15[/C][/ROW]
[ROW][C]0.271[/C][C]-3.33176821822752e-14[/C][C]4.56399231814795e-15[/C][/ROW]
[ROW][C]0.281[/C][C]-3.04003989071257e-14[/C][C]5.63254725597742e-15[/C][/ROW]
[ROW][C]0.291[/C][C]-2.72001053808414e-14[/C][C]5.54212909569742e-15[/C][/ROW]
[ROW][C]0.301[/C][C]-2.43605979001261e-14[/C][C]4.45567056707476e-15[/C][/ROW]
[ROW][C]0.311[/C][C]-2.22290537319759e-14[/C][C]3.15959337621131e-15[/C][/ROW]
[ROW][C]0.321[/C][C]-2.072426254491e-14[/C][C]2.30649169517481e-15[/C][/ROW]
[ROW][C]0.331[/C][C]-1.9522339558008e-14[/C][C]2.12829723213232e-15[/C][/ROW]
[ROW][C]0.341[/C][C]-1.82854477976511e-14[/C][C]2.47834518231043e-15[/C][/ROW]
[ROW][C]0.351[/C][C]-1.68372425619243e-14[/C][C]2.91943457511274e-15[/C][/ROW]
[ROW][C]0.361[/C][C]-1.52365040383128e-14[/C][C]3.04537589748988e-15[/C][/ROW]
[ROW][C]0.371[/C][C]-1.36738982706708e-14[/C][C]2.79930341890972e-15[/C][/ROW]
[ROW][C]0.381[/C][C]-1.22981728389661e-14[/C][C]2.37874811940578e-15[/C][/ROW]
[ROW][C]0.391[/C][C]-1.11654044407228e-14[/C][C]1.91276650262423e-15[/C][/ROW]
[ROW][C]0.401[/C][C]-1.02917803407426e-14[/C][C]1.42300876305275e-15[/C][/ROW]
[ROW][C]0.411[/C][C]-9.66810037200523e-15[/C][C]9.81988602577306e-16[/C][/ROW]
[ROW][C]0.421[/C][C]-9.23646068119357e-15[/C][C]6.95886105061769e-16[/C][/ROW]
[ROW][C]0.431[/C][C]-8.90619151762771e-15[/C][C]5.91975059571109e-16[/C][/ROW]
[ROW][C]0.441[/C][C]-8.5915460618854e-15[/C][C]6.38619192265022e-16[/C][/ROW]
[ROW][C]0.451[/C][C]-8.2188104243122e-15[/C][C]8.25111669671241e-16[/C][/ROW]
[ROW][C]0.461[/C][C]-7.71892214504633e-15[/C][C]1.13979970287138e-15[/C][/ROW]
[ROW][C]0.471[/C][C]-7.02952615624256e-15[/C][C]1.56974758969107e-15[/C][/ROW]
[ROW][C]0.481[/C][C]-6.06711236689348e-15[/C][C]2.22572670294611e-15[/C][/ROW]
[ROW][C]0.491[/C][C]-4.65634945831946e-15[/C][C]3.35683422962229e-15[/C][/ROW]
[ROW][C]0.501[/C][C]-2.53562143244171e-15[/C][C]5.00359715069001e-15[/C][/ROW]
[ROW][C]0.511[/C][C]4.40759853389716e-16[/C][C]6.62793767890865e-15[/C][/ROW]
[ROW][C]0.521[/C][C]4.03736355546896e-15[/C][C]7.33389865931624e-15[/C][/ROW]
[ROW][C]0.531[/C][C]7.63941257226886e-15[/C][C]6.64378987346235e-15[/C][/ROW]
[ROW][C]0.541[/C][C]1.06186284045737e-14[/C][C]4.99165075011006e-15[/C][/ROW]
[ROW][C]0.551[/C][C]1.27328500928277e-14[/C][C]3.34424620587678e-15[/C][/ROW]
[ROW][C]0.561[/C][C]1.41929988284322e-14[/C][C]2.42890212966976e-15[/C][/ROW]
[ROW][C]0.571[/C][C]1.54139541840457e-14[/C][C]2.3506794232542e-15[/C][/ROW]
[ROW][C]0.581[/C][C]1.67364973415372e-14[/C][C]2.76158042130323e-15[/C][/ROW]
[ROW][C]0.591[/C][C]1.83128873630605e-14[/C][C]3.27740975886432e-15[/C][/ROW]
[ROW][C]0.601[/C][C]2.01334839154135e-14[/C][C]3.65538822601214e-15[/C][/ROW]
[ROW][C]0.611[/C][C]2.20910648800516e-14[/C][C]3.76679398756444e-15[/C][/ROW]
[ROW][C]0.621[/C][C]2.40300590522192e-14[/C][C]3.55983557768553e-15[/C][/ROW]
[ROW][C]0.631[/C][C]2.57832900814734e-14[/C][C]3.05048009137407e-15[/C][/ROW]
[ROW][C]0.641[/C][C]2.72073049194018e-14[/C][C]2.32112171831493e-15[/C][/ROW]
[ROW][C]0.651[/C][C]2.82221577439267e-14[/C][C]1.52740951921935e-15[/C][/ROW]
[ROW][C]0.661[/C][C]2.88471307198414e-14[/C][C]8.69548428308428e-16[/C][/ROW]
[ROW][C]0.671[/C][C]2.92062049253009e-14[/C][C]5.19739095164953e-16[/C][/ROW]
[ROW][C]0.681[/C][C]2.94956906122346e-14[/C][C]5.81395166979416e-16[/C][/ROW]
[ROW][C]0.691[/C][C]2.9926437881005e-14[/C][C]1.00123194916502e-15[/C][/ROW]
[ROW][C]0.701[/C][C]3.06333208968873e-14[/C][C]1.52493926600296e-15[/C][/ROW]
[ROW][C]0.711[/C][C]3.157897435446e-14[/C][C]1.80374080154156e-15[/C][/ROW]
[ROW][C]0.721[/C][C]3.27113441897778e-14[/C][C]2.39909210648357e-15[/C][/ROW]
[ROW][C]0.731[/C][C]4.40649459008942e-14[/C][C]6.28560516523661e-14[/C][/ROW]
[ROW][C]0.741[/C][C]5.98386038566594e-13[/C][C]3.04823537581402e-12[/C][/ROW]
[ROW][C]0.751[/C][C]2.20131288029649e-11[/C][C]1.09465449934681e-10[/C][/ROW]
[ROW][C]0.761[/C][C]6.26513798649962e-10[/C][C]2.84970572451632e-09[/C][/ROW]
[ROW][C]0.771[/C][C]1.30038356406424e-08[/C][C]5.33848223179988e-08[/C][/ROW]
[ROW][C]0.781[/C][C]1.95551993380109e-07[/C][C]7.13855116464639e-07[/C][/ROW]
[ROW][C]0.791[/C][C]2.11969682847511e-06[/C][C]6.75086419204585e-06[/C][/ROW]
[ROW][C]0.801[/C][C]1.64873174385999e-05[/C][C]4.46819189586174e-05[/C][/ROW]
[ROW][C]0.811[/C][C]9.17581606139275e-05[/C][C]0.00020461475678841[/C][/ROW]
[ROW][C]0.821[/C][C]0.000365605260800141[/C][C]0.000640435375114125[/C][/ROW]
[ROW][C]0.831[/C][C]0.00105027366361769[/C][C]0.00135329260197506[/C][/ROW]
[ROW][C]0.841[/C][C]0.00221494966835012[/C][C]0.00190880712769662[/C][/ROW]
[ROW][C]0.851[/C][C]0.00355327091874818[/C][C]0.00178614265259263[/C][/ROW]
[ROW][C]0.861[/C][C]0.0045992436606155[/C][C]0.00113227906163434[/C][/ROW]
[ROW][C]0.871[/C][C]0.00519687761243099[/C][C]0.000563259961054099[/C][/ROW]
[ROW][C]0.881[/C][C]0.0055247115510981[/C][C]0.000334524812094888[/C][/ROW]
[ROW][C]0.891[/C][C]0.00577429901708017[/C][C]0.000291535374540362[/C][/ROW]
[ROW][C]0.901[/C][C]0.00603311665627967[/C][C]0.000316217297831294[/C][/ROW]
[ROW][C]0.911[/C][C]0.00633363834485001[/C][C]0.000347637636964456[/C][/ROW]
[ROW][C]0.921[/C][C]0.00663737976262003[/C][C]0.000295777459384629[/C][/ROW]
[ROW][C]0.931[/C][C]0.00688137737772975[/C][C]0.000209065607322487[/C][/ROW]
[ROW][C]0.941[/C][C]0.00709865988761633[/C][C]0.000216773425977669[/C][/ROW]
[ROW][C]0.951[/C][C]0.00758050685644743[/C][C]0.000632431823998246[/C][/ROW]
[ROW][C]0.961[/C][C]0.00897057114426532[/C][C]0.00141486711553062[/C][/ROW]
[ROW][C]0.971[/C][C]0.0116940473474218[/C][C]0.00212194631990681[/C][/ROW]
[ROW][C]0.981[/C][C]0.0169720596583597[/C][C]0.00387446213985401[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=91684&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=91684&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
0.001-0.01389661461577870.000367573518046186
0.011-0.008183264683430570.000867978872809949
0.021-0.007161393688912430.000104258672558594
0.031-0.006981545507510180.000142378710696068
0.041-0.006745988156719650.000207954892221286
0.051-0.006414358583557620.000332483665325154
0.061-0.006031502031853150.000320499722917276
0.071-0.005708230381090360.000293168021502747
0.081-0.005384917081620760.000411800067253306
0.091-0.004808389224490490.00100312341398463
0.101-0.003597477161182530.00187509715756753
0.111-0.001957976475059440.00192645309911412
0.121-0.0007057145773367740.00107538701136083
0.131-0.0001614828822013070.000337062187387916
0.141-2.31984250601023e-056.13630461862344e-05
0.151-2.10086716285627e-066.68750442062184e-06
0.161-1.21247332650576e-074.48036338669822e-07
0.171-4.52043555240645e-091.8890359820965e-08
0.181-1.10487203289753e-105.11794343177028e-10
0.191-1.83896313561993e-129.07894201249133e-12
0.201-6.37693498231092e-141.08849140543908e-13
0.211-4.27562831407604e-143.15848815787168e-15
0.221-4.10220380021872e-142.54967089401847e-15
0.231-3.95149465485271e-142.3079799458643e-15
0.241-3.82022478209831e-142.01611346955311e-15
0.251-3.69817882131336e-142.14726041961129e-15
0.261-3.54911875812555e-143.08969753028979e-15
0.271-3.33176821822752e-144.56399231814795e-15
0.281-3.04003989071257e-145.63254725597742e-15
0.291-2.72001053808414e-145.54212909569742e-15
0.301-2.43605979001261e-144.45567056707476e-15
0.311-2.22290537319759e-143.15959337621131e-15
0.321-2.072426254491e-142.30649169517481e-15
0.331-1.9522339558008e-142.12829723213232e-15
0.341-1.82854477976511e-142.47834518231043e-15
0.351-1.68372425619243e-142.91943457511274e-15
0.361-1.52365040383128e-143.04537589748988e-15
0.371-1.36738982706708e-142.79930341890972e-15
0.381-1.22981728389661e-142.37874811940578e-15
0.391-1.11654044407228e-141.91276650262423e-15
0.401-1.02917803407426e-141.42300876305275e-15
0.411-9.66810037200523e-159.81988602577306e-16
0.421-9.23646068119357e-156.95886105061769e-16
0.431-8.90619151762771e-155.91975059571109e-16
0.441-8.5915460618854e-156.38619192265022e-16
0.451-8.2188104243122e-158.25111669671241e-16
0.461-7.71892214504633e-151.13979970287138e-15
0.471-7.02952615624256e-151.56974758969107e-15
0.481-6.06711236689348e-152.22572670294611e-15
0.491-4.65634945831946e-153.35683422962229e-15
0.501-2.53562143244171e-155.00359715069001e-15
0.5114.40759853389716e-166.62793767890865e-15
0.5214.03736355546896e-157.33389865931624e-15
0.5317.63941257226886e-156.64378987346235e-15
0.5411.06186284045737e-144.99165075011006e-15
0.5511.27328500928277e-143.34424620587678e-15
0.5611.41929988284322e-142.42890212966976e-15
0.5711.54139541840457e-142.3506794232542e-15
0.5811.67364973415372e-142.76158042130323e-15
0.5911.83128873630605e-143.27740975886432e-15
0.6012.01334839154135e-143.65538822601214e-15
0.6112.20910648800516e-143.76679398756444e-15
0.6212.40300590522192e-143.55983557768553e-15
0.6312.57832900814734e-143.05048009137407e-15
0.6412.72073049194018e-142.32112171831493e-15
0.6512.82221577439267e-141.52740951921935e-15
0.6612.88471307198414e-148.69548428308428e-16
0.6712.92062049253009e-145.19739095164953e-16
0.6812.94956906122346e-145.81395166979416e-16
0.6912.9926437881005e-141.00123194916502e-15
0.7013.06333208968873e-141.52493926600296e-15
0.7113.157897435446e-141.80374080154156e-15
0.7213.27113441897778e-142.39909210648357e-15
0.7314.40649459008942e-146.28560516523661e-14
0.7415.98386038566594e-133.04823537581402e-12
0.7512.20131288029649e-111.09465449934681e-10
0.7616.26513798649962e-102.84970572451632e-09
0.7711.30038356406424e-085.33848223179988e-08
0.7811.95551993380109e-077.13855116464639e-07
0.7912.11969682847511e-066.75086419204585e-06
0.8011.64873174385999e-054.46819189586174e-05
0.8119.17581606139275e-050.00020461475678841
0.8210.0003656052608001410.000640435375114125
0.8310.001050273663617690.00135329260197506
0.8410.002214949668350120.00190880712769662
0.8510.003553270918748180.00178614265259263
0.8610.00459924366061550.00113227906163434
0.8710.005196877612430990.000563259961054099
0.8810.00552471155109810.000334524812094888
0.8910.005774299017080170.000291535374540362
0.9010.006033116656279670.000316217297831294
0.9110.006333638344850010.000347637636964456
0.9210.006637379762620030.000295777459384629
0.9310.006881377377729750.000209065607322487
0.9410.007098659887616330.000216773425977669
0.9510.007580506856447430.000632431823998246
0.9610.008970571144265320.00141486711553062
0.9710.01169404734742180.00212194631990681
0.9810.01697205965835970.00387446213985401


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.001 ; par2 = 0.99 ; par3 = 0.01 ;
Parameters (R input):
par1 = 0.001 ; 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')