[R] univariate normal mixtures

[Pikounis, Bill]

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

v_bill_pikounis at merck.com

Phone: 732 594 3913
Fax: 732 594 1565


> -----Original Message-----
> From: Joke Allemeersch [mailto:Joke.Allemeersch at esat.kuleuven.ac.be] 
> Sent: Thursday, July 17, 2003 11:58 AM
> To: r-help at stat.math.ethz.ch
> 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.
> 
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