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> 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 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.
