Hi Kevin, a more or less established method (at least for normal mixtures) is the use of the Bayesian information criterion BIC defined as maximization of 2* max loglikelihood (s) -log(n)*number of fitted parameters for model s, s being the number of components, n number of points, over s. However I have no experience with it in connection with exponential mixtures.
Christian On Wed, 30 Jul 2003, kevin xie wrote: > Dear all, > > I'm fitting a set of length-of-stay data by a model of mixture of > exponentials. I've been following the example on page 436 in MASS (5th Ed.). > However, I have a couple of questions while following this example. > > What if we don't know how many components there are in the model in advance. > Is there any established method to determine the number of components from a > set of data? I'm aware that the usual likelihood ratio test is not > appropriate in this case due to the possibility that the ML could occur at > the boundry of the parameter space. > > Secondly, the example in MASS uses a Q-Q plot to informally assess GOF. I > was wondering if there are some more formal statistical tests for this > purpose. > > I appologise for asking questions that are slightly out-of-topic. > > Many thanks. > > Kevin > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > *********************************************************************** Christian Hennig Seminar fuer Statistik, ETH-Zentrum (LEO), CH-8092 Zuerich (current) and Fachbereich Mathematik-SPST/ZMS, Universitaet Hamburg [EMAIL PROTECTED], http://stat.ethz.ch/~hennig/ [EMAIL PROTECTED], http://www.math.uni-hamburg.de/home/hennig/ ####################################################################### ich empfehle www.boag.de ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
