I'm looking for goodness of fit tests for gamma distributions with large data sizes and for different data. I have a matrix with around 4.000 data values about losses and there is a heavy right-tail in it. I have fitted a gamma distribution with "fitdistr".
You can see the example: fitdistr(corpo,"gamma",lower=0.001) Errore in optim(x = c(5000, 5000, 5000, 5000, 5000, 5000, 5000, 5000, 5000, : non-finite finite-difference value [2] The problem is the optimization for the test with different data. In summary - how to estimate the parameters? - is there another way to estimate the gamma parameters that doesnt depend on the sample size? -- View this message in context: http://r.789695.n4.nabble.com/Fitting-Gamma-distribution-tp2265313p2265313.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.
