Hi Thierry Thanks for clarifiyng. I spoke about using ecdf because it gives me possibility to calculate proportion of objects below some threshold (quantiles) quite easily.
quantInv <- function(distr, value) ecdf(distr)(value) > quantInv(x,80)*100 [1] 57.14286 I believe that such value could be calculated from this cumsum construction too. However with real data (hundereds of "x" values), Ecdf and wtd.quantile works quite good so I can live without it (I do not want to reinvent wheel). Thanks again. Cheers Petr > -----Original Message----- > From: Thierry Onkelinx [mailto:thierry.onkel...@inbo.be] > Sent: Friday, November 24, 2017 10:02 PM > To: PIKAL Petr <petr.pi...@precheza.cz> > Cc: Duncan Murdoch <murdoch.dun...@gmail.com>; r-help@r-project.org > Subject: Re: [R] number to volume weighted distribution > > Hi Petr, > > I think that Duncan suggests something like this: > > x<- c(rep(10,20), rep(300,5), rep(100, 10)) tx <- table(x) > > prop.x <- tx / sum(tx) > vx <- as.integer(names(tx)) > prop.wx <- tx * vx / sum(tx * vx) > > plot(ecdf(x)) > plot(vx, cumsum(prop.x), ylim = 0:1) > plot(vx, cumsum(prop.wx), ylim = 0:1) > > Best regards, > > Thierry > > ir. Thierry Onkelinx > Statisticus / Statistician > > Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN > BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team > Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance > thierry.onkel...@inbo.be Kliniekstraat 25, B-1070 Brussel www.inbo.be > > > > > 2017-11-24 14:30 GMT+01:00 PIKAL Petr <petr.pi...@precheza.cz>: > > Hi Duncan > > > > I tried Ecdf and/or wtd.quantile from Hmisc and it is working (probably). > > Ecdf(x, q=.5) > > Ecdf(x, weights=xw,col=2, add=T, q=.5) > > wtd.quantile(x) > > 0% 25% 50% 75% 100% > > 10 10 10 100 300 > > wtd.quantile(x, weights=xw, type="i/n") > > 0% 25% 50% 75% 100% > > 10.0000 138.8667 192.5778 246.2889 300.0000 > > > > But could you please be more specific in this? > > > >> But you seem to be asking about a > >> definition rather than a function: it is obtained simply by > >> normalizing the weights to sum to 1, then evaluating cumulative sums of > them. > > > > Actually, when I correctly calculate weights > > > > xw <- (x^3)/sum(x^3) > > sum(xw) equals to 1 > > > > but how can I plot ecdf with volume weighted data. Obviously > > > > ecdf(x*xw) or ecdf(x^3*xw) is not correct. > > > > Cheers > > Petr > > > >> -----Original Message----- > >> From: Duncan Murdoch [mailto:murdoch.dun...@gmail.com] > >> Sent: Friday, November 24, 2017 12:36 PM > >> To: PIKAL Petr <petr.pi...@precheza.cz>; r-help@r-project.org > >> Subject: Re: [R] number to volume weighted distribution > >> > >> On 24/11/2017 6:27 AM, PIKAL Petr wrote: > >> > Dear all > >> > > >> > Strictly speaking it is not R question but as you are the most > >> > capable persons I > >> know I give it a try. > >> > > >> > I am strugling with recalculation of number weighted to volume > >> > weighted > >> distribution. > >> > > >> > Suppose I have objects (cubes) with size > >> > > >> > x<- c(rep(10,20), rep(100, 10), rep(300,5)) I can get > >> > > >> > plot(ecdf(x)) > >> > > >> > or the number weighted average > >> > > >> > mean(x) > >> > [1] 77.14286 > >> > > >> > or volume weighted average > >> > weighted.mean(x, (x/sum(x^3))) > >> > [1] 204.4444 > >> > > >> > However I am struggling with volume weighted ecdf. > >> > > >> > Can you please give me some hints? > >> > >> I believe base R doesn't have a function for this, but Google says it > >> exists in a couple of packages: spatstat, Hmisc. But you seem to be > >> asking about a definition rather than a function: it is obtained > >> simply by normalizing the weights to sum to 1, then evaluating cumulative > sums of them. > >> > >> Duncan Murdoch > > ________________________________ Tento e-mail a jakékoliv k němu připojené dokumenty jsou důvěrné a jsou určeny pouze jeho adresátům. Jestliže jste obdržel(a) tento e-mail omylem, informujte laskavě neprodleně jeho odesílatele. Obsah tohoto emailu i s přílohami a jeho kopie vymažte ze svého systému. Nejste-li zamýšleným adresátem tohoto emailu, nejste oprávněni tento email jakkoliv užívat, rozšiřovat, kopírovat či zveřejňovat. Odesílatel e-mailu neodpovídá za eventuální škodu způsobenou modifikacemi či zpožděním přenosu e-mailu. 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