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Harrell-Davis Percentielen Inschrijvingen nieuwe personenwagens

*Unverified author*
R Software Module: /rwasp_harrell_davis.wasp (opens new window with default values)
Title produced by software: Harrell-Davis Quantiles
Date of computation: Mon, 08 Mar 2010 07:59:01 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Mar/08/t1268060511ihxqvyw0ot5nico.htm/, Retrieved Mon, 08 Mar 2010 16:01:52 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Mar/08/t1268060511ihxqvyw0ot5nico.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
KDGP1W41
 
Dataseries X:
» Textbox « » Textfile « » CSV «
41086 39690 43129 37863 35953 29133 24693 22205 21725 27192 21790 13253 37702 30364 32609 30212 29965 28352 25814 22414 20506 28806 22228 13971 36845 35338 35022 34777 26887 23970 22780 17351 21382 24561 17409 11514 31514 27071 29462 26105 22397 23843 21705 18089 20764 25316 17704 15548 28029 29383 36438 32034 22679 24319 18004 17537 20366 22782 19169 13807 29743 25591 29096 26482 22405 27044 17970 18730 19684 19785 18479 10698
 
Output produced by software:


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
0.0111059.3484065897991.350605640521
0.0211674.78225892661230.37935213976
0.0312390.69571172121353.82824830105
0.0413104.50209886281402.15421663614
0.0513780.45373203301467.61736618736
0.0614418.05536661171552.58207510521
0.0715021.65227622211598.94164518580
0.0815586.77485814061562.65178352080
0.0916101.31472862811440.58682460262
0.116553.14030344201261.71904227439
0.1116936.68664920081067.56369847615
0.1217255.2495304785895.55882543022
0.1317519.4043359949770.319231899822
0.1417743.5729286899701.121997123637
0.1517942.6188408457683.748556778319
0.1618129.4759351281705.821645094099
0.1718313.9938103834753.0540340243
0.1818502.7282459787813.13380860703
0.1918699.2897031691876.567489014757
0.218904.9333628657936.419353564739
0.2119119.1932937618988.01438681905
0.2219340.46000671541028.46162648322
0.2319566.45905204291056.32875279131
0.2419794.61893472891071.36886882921
0.2520022.33353148211073.95955517490
0.2620247.13535117611064.86200898146
0.2720466.80307651271045.14496745306
0.2820679.42886423751016.06865596881
0.2920883.4673808364979.138464638474
0.321077.7807959141936.211321502927
0.3121261.6845597114889.519434469783
0.3221434.9905166419841.72501271247
0.3321598.0386363085795.735027591683
0.3421751.7069651112754.724283749435
0.3521897.3908142462721.703428349759
0.3622036.9456629775699.57734886182
0.3722172.5927317214690.527435790768
0.3822306.7909256652695.906841231938
0.3922442.0834102571715.975761025028
0.422580.9310873708749.572903183123
0.4122725.5482208239794.55463519756
0.4222877.7567918475847.905425269504
0.4323038.8752445207906.103323075585
0.4423209.6538050712965.61089134156
0.4523390.26278540351023.05992141788
0.4623580.33311724901075.64199829487
0.4723779.04120849471121.23745974102
0.4823985.22459298261158.51129983413
0.4924197.51195806911186.91729883597
0.524414.4514770231206.61986807374
0.5124634.62457925461218.21972712550
0.5224856.73724402061222.78627422587
0.5325079.68608850291221.56947534336
0.5425302.60050221241215.87713300222
0.5525524.86394324181207.10595269668
0.5625746.11714659601196.66028337275
0.5725966.24411694181185.78598161617
0.5826185.33969405361175.78330699272
0.5926403.65664876681167.41156871284
0.626621.53178853821161.24460010690
0.6126839.29471955351157.09053311131
0.6227057.16899496571154.20221910818
0.6327275.18171221381151.07480955972
0.6427493.10203557221145.95376453736
0.6527710.42959717081136.8038163361
0.6627926.44911249321122.17545955824
0.6728140.3580329991101.38109225907
0.6828351.46128795271075.02400326327
0.6928559.41380743411045.15249078615
0.728764.48045991421015.35169792374
0.7128967.7764739702990.534225522678
0.7229171.4501631480976.663092240636
0.7329378.7731490473979.822473221855
0.7429594.10961495251005.67558974559
0.7529822.74380666881058.25221326884
0.7630070.55360735861139.05475072899
0.7730343.52904281911246.58625693503
0.7830647.15121286571375.99438495967
0.7930985.67278256651519.1736162208
0.831361.37668237891665.03966210523
0.8131773.93023653431800.30311075661
0.8232219.98495141081910.64956295551
0.8332693.1784573911982.86456507682
0.8433184.65519651492007.03973757493
0.8533684.12806813841979.13040201783
0.8634181.36959759171902.34340298084
0.8734667.89293181561787.39180081037
0.8835138.5244761261650.97845829136
0.8935592.63410728721512.74945790330
0.936034.96789361461391.99079053831
0.9136476.21051192591305.32036115541
0.9236933.392392811266.71863519572
0.9337429.92230948381287.88365447509
0.9437994.59194846371373.18113188833
0.9538658.92937254441506.46503580400
0.9639452.37727955181643.64889531013
0.9740391.01082922141735.5136063207
0.9841443.63859905881787.20286814423
0.9942459.70690806461881.07324733223
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Mar/08/t1268060511ihxqvyw0ot5nico/1axzm1268060340.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Mar/08/t1268060511ihxqvyw0ot5nico/1axzm1268060340.ps (open in new window)


 
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')
 





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