Joke, Two other places to help you with your objectives in fitting univariate normal mixtures are:
1) The mclust package by Raftery and Fraley (available at CRAN). Their EMclust() function, for example, lets you specify a range of "number of components" to fit multiple models as well as the ability to specify whether to assume equal variances or not. The Schwarz (BIC / SBC) criterion is used to help distinguish goodness-of-fit amongst the models fitted. I have found the fitting routines to be more-than-quick enough under Linux, but did run into problems when running the same code under Windows. 2) The Venables & Ripley MASS book, Editions 4 and earlier, provide a very educational and useful discussion of analyses of mixture models beyond the fitting considerations (which are nicely covered as well). I do not have my book copy with me at the moment, but I believe in the 4th edition the material is covered in the last chapter entitled "Optimization". Hope that Helps. Best Regards, Bill ---------------------------------------- Bill Pikounis, Ph.D. Biometrics Research Department Merck Research Laboratories PO Box 2000, MailDrop RY33-300 126 E. Lincoln Avenue Rahway, New Jersey 07065-0900 USA [EMAIL PROTECTED] Phone: 732 594 3913 Fax: 732 594 1565 > -----Original Message----- > From: Joke Allemeersch [mailto:[EMAIL PROTECTED] > Sent: Thursday, July 17, 2003 11:58 AM > To: [EMAIL PROTECTED] > Subject: [R] univariate normal mixtures > > > Hello, > > I have a concrete statistical question: > I have a sample of an univariate mixture of an unknown number (k) of > normal distributions, each time with an unknown mean `m_i' and a > standard deviation `k * m_i', where k is known factor > constant for all > the normal distributions. (The `i' is a subscript.) > Is there a function in R that can estimate the number of normal > distributions k and the means `m_i' for the different normal > distributions from a sample? Or evt. a function that can > estimate the > `m_i', when the number of distributions `k' is known? > So far I only found a package, called `normix'. But at first > sight it > only provides methods to sample from such distributions and > to estimate > the densities; but not to fit such a distribution. > Can someone indicate where I can find an elegant solution? > > Thank you in advance > > Joke Allemeersch > > Katholieke universiteit Leuven. > Belgium. > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > ------------------------------------------------------------------------------ Notice: This e-mail message, together with any attachments, ...{{dropped}} ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
