Thanks for that Remko, but im slightly confused because isnt this testing the goodness of fit of 2 slightly different gamma distributions, not of how well a gamma distribution is representing the data.
e.g. data.vec<-as.vector(data) (do some mle to find the parameters of a gamma distribution for data.vec) xrarea<-seq(-2,9,0.05) yrarea<-dgamma(xrarea,shape=7.9862,rate=2.6621) so now yrarea is the gamma distribution and i want to compare it with data.vec to see how well it fits. regards, Dann Remko Duursma-2 wrote: > > Hi Dann, > > there is probably a better way to do this, but this works anyway: > > # your data > gamdat <- rgamma(10000, shape=1, rate=0.5) > > # comparison to gamma: > gamsam <- rgamma(10000, shape=1, rate=0.6) > > qqplot(gamsam,gamdat) > abline(0,1) > > > greetings > Remko > > > ------------------------------------------------- > Remko Duursma > Post-Doctoral Fellow > > Centre for Plant and Food Science > University of Western Sydney > Hawkesbury Campus > Richmond NSW 2753 > > Dept of Biological Science > Macquarie University > North Ryde NSW 2109 > Australia > > Mobile: +61 (0)422 096908 > > > > On Tue, Jan 27, 2009 at 3:38 AM, Dan31415 <d.m.mitch...@reading.ac.uk> > wrote: >> >> I'm looking for goodness of fit tests for gamma distributions with large >> data >> sizes. I have a matrix with around 10,000 data values in it and i have >> fitted a gamma distribution over a histogram of the data. >> >> The problem is testing how well that distribution fits. Chi-squared seems >> to >> be used more for discrete distributions and kolmogorov-smirnov seems that >> large sample sizes make it had to evaluate the D statistic. Also i >> haven't >> found a qq plot for gamma, although i think this might be an appropriate >> test. >> >> in summary >> -is there a gamma goodness of fit test that doesnt depend on the sample >> size? >> -is there a way of using qqplot for gamma distributions, if so how would >> you >> calculate it from a matrix of data values? >> >> regards, >> Dann >> -- >> View this message in context: >> http://www.nabble.com/Goodness-of-fit-for-gamma-distributions-tp21668711p21668711.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. >> > > ______________________________________________ > 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. > > -- View this message in context: http://www.nabble.com/Goodness-of-fit-for-gamma-distributions-tp21668711p21686095.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.
