On Feb 10, 2014, at 6:34 AM, Bert Gunter wrote: > I believe this is more a question for SO (stats.stackexchange.com).
Actually it might get closed on SO since it is not an R programming question per se but rather an advice for statistical approach. It's a better fit for CrossValidated.com > There are many possible goodness of fit statistics that can easily be > calculated in R, but I think the fundamental question is: To what end? > First, there are probably several parametric distributions that give > (essentially) equally good fits; and second, you may want none of > them, preferring some sort of nonparametric fit. Again, the sort of > thing that is probably better at SO -- or even better, with a local > statistician. > Cheers, > Bert > > Bert Gunter > Genentech Nonclinical Biostatistics > (650) 467-7374 > > "Data is not information. Information is not knowledge. And knowledge > is certainly not wisdom." > H. Gilbert Welch > > > > > On Mon, Feb 10, 2014 at 12:25 AM, Alaios <ala...@yahoo.com> wrote: >> Hi all, >> I have a large number of measurements from which I select a large number of >> unique vectors. For each vectors I would like to test which distribution >> might be a candidate for fitting. >> It is impossible to look on each vector separately but I can inside a for >> loop test different models and based on their goodness of fit to make >> offline decisions (I will be saving goodness of fits results on a text file). >> >> Do you know given a vector how I can get the goodness of fit for the "basic" >> distributions : "norm", "lnorm", "pois", "exp", "gamma", "nbinom", >> "geom", "beta", "unif" and "logis" >> >> Is it possible to try many of those (or at least some of the above) and try >> to get these results? >> >> Regards >> Alex >> [[alternative HTML version deleted]] > David Winsemius Alameda, CA, USA ______________________________________________ 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.
