If you try more than one or two distributions the final estimates, while appearing to have higher precision that the ECDF, will actually have the same precision. That is because of model uncertainty. This would be revealed by bootstrapping. There is little advantage to using a parametric model if nonparametric estimates are used as touchstones.
Frank Lathouri, Maria wrote: > > Hallo > yes I tried it as well and it works; > > Thank you a lot > > Maria > > ________________________________ > From: Dennis Murphy [djmu...@gmail.com] > Sent: 15 March 2011 21:36 > To: Lathouri, Maria > Cc: r-help@r-project.org > Subject: Re: [R] fitting a distribution to a ecdf plot > > Hi: > > The fitdistrplus package from CRAN may be useful. I tried it on your data > and the lognormal seemed to fit well, apart from the outlier. I just > followed the vignette that accompanies the package. > > library(fitdistplus) > > plotdist(NOEccu) # ecdf > descdist(NOEccu, boot = 1000) # Cullen-Frey graph based on 1000 > bootstrap samples > > # The Cullen-Frey graph suggests that the distribution is somewhere > between a Gamma and lognormal > > # Weibull > N1w <- fitdist(NOEccu, 'weibull') > # Warning messages: > # 1: In dweibull(x, shape, scale, log) : NaNs produced > # 2: In dweibull(x, shape, scale, log) : NaNs produced > plot(N1w) > summary(N1w) > > # Gamma > N1g <- fitdist(NOEccu, 'gamma') > # Warning messages: > # 1: In dgamma(x, shape, scale, log) : NaNs produced > # 2: In dgamma(x, shape, scale, log) : NaNs produced > # 3: In dgamma(x, shape, scale, log) : NaNs produced > # 4: In dgamma(x, shape, scale, log) : NaNs produced > plot(N1g) > summary(N1g) > > # Lognormal > N1l <- fitdist(NOEccu, 'lnorm') > plot(N1l) > summary(N1l) > > Try it out and see if it suits your needs. > > HTH, > Dennis > > On Tue, Mar 15, 2011 at 9:00 AM, Lathouri, Maria > <m.lathour...@imperial.ac.uk<mailto:m.lathour...@imperial.ac.uk>> > wrote: > Dear all, > > I need to plot an cumulative distribution plot of a variable and then to > fit a distribution to that, probably a weibull or lognormal. > > I have plotted the ecdf as >> plot(ecdf(x)) > > but I haven't managed to fit the distribution. I have as well attached the > data. > > I would appreciate if you could help me on that. > > Thank you. > > Kind regards > Maria > > ______________________________________________ > R-help@r-project.org<mailto:R-help@r-project.org> mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/fitting-a-distribution-to-a-ecdf-plot-tp3357015p3357954.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
