Thanks Timur While assessing whether or not the best option would be a normal distribution (it won't be, the data in this case LOOKS more poisson, or if I explude the first week of results, a negative exponential; and in my other case, cauchy is more likely), I really need a test that can be applied regardless of the distribution to see which distribution fits best. Using log-likelihood, there doesn't seem to be much to choose between exponential and poisson (the log-likelihhod for them being almost the same, regardless of the sample even tough the parameters are very different from one sample to the next - I don't understand why yet), and the others I have tried are MUCH worse, but I'm not done yet.
Are you aware of functions that allow estimation of all the parameters of a non-central distribution? I ask because a problem I'll be working on in a few weeks will involve the kind of skew produced by a non-central distribution (among others). I see some functions allow you to work with skewed distributions (e.g. "[dpqr]stable the skewed stable distribution ") but I have not yet found functions that alow one to estimate their parameters from real data. Thanks, Ted Timur Shtatland wrote: > > If one of the goals is the normality test, then there may be better > alternatives to the Kolmogorov-Smirnov test. > See an explanation on: > http://graphpad.com/FAQ/viewfaq.cfm?faq=959 > > The R implementation: > ?shapiro.test > > A casual search also turned this up: > http://tolstoy.newcastle.edu.au/R/help/04/09/3201.html > http://tolstoy.newcastle.edu.au/R/help/04/08/3121.html > http://www.karlin.mff.cuni.cz/~pawlas/2008/MAI061/dagost.R > > Best, > > Timur > -- > Timur Shtatland, Ph.D. > Senior Bioinformatics Scientist > Agencourt Bioscience Corporation - A Beckman Coulter Company > 500 Cummings Center, Suite 2450 > Beverly, MA 01915 > www.agencourt.com > > On Mon, Sep 22, 2008 at 12:26 PM, Ted Byers <[EMAIL PROTECTED]> wrote: >> >> I am in a situation where I have to fit a distrution, such as cauchy or >> normal, to an empirical dataset. Well and good, that is easy. >> >> But I wanted to assess just how good the fit is, using ks.test. >> >> I am concerned about the following note in the docs (about the example >> provided): "Note that the distribution theory is not valid here as we >> have >> estimated the parameters of the normal distribution from the same sample" >> >> This implies I should not use ks.test(x,"pnorm",mean =1.187, sd =0.917), >> where the numbers shown are estimated from 'x'. If this is so, how do I >> get >> a correct test? I know I can not use different samples because of just >> how >> different the parameters are from one sample to the next, so using >> parameters estimated from the sample from week one to define the >> distribution function for ks.test will give a poor fit for the data from >> week two. And the sample size is small enough that I would not have >> confidence in the parameters estimated from a portion of a samlpe to fit >> against the remainder of the sample. >> >> Thanks >> >> Ted >> >> -- >> View this message in context: >> http://www.nabble.com/Statistical-question-re-assessing-fit-of-distribution-functions.-tp19611539p19611539.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/Statistical-question-re-assessing-fit-of-distribution-functions.-tp19611539p19629108.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.
