Hi Mike,
I have an EM algorithm code for a binary von Mises mixture with 5 parameters:
mixing proportion (p), 2 locations (m1, m2), and 2 dispersion parameters (k1,
k2). Of course, your model is nested within this one, where k1=Inf, m1 =
arbitrary, m2=0. You should be able to modify my code easily to fit this
reduced model. This will also allow you to perform a likelihood ratio test for
whether the 5-parameter model is better than the 2-parameter model
(approximately chi-squared with 3 d.o.f.).
Alternatively, you can directly estimate the 2-parameter model by maximizing
the log-likelihood subject to constraints on the 2 parameters. This is quite
easy to do, but will not allow you comparison with a more general model.
Ravi.
Ravi Varadhan, Ph.D.
Assistant Professor,
Division of Geriatric Medicine and Gerontology
School of Medicine
Johns Hopkins University
Ph. (410) 502-2619
email: rvarad...@jhmi.edu
- Original Message -
From: Mike Lawrence mike.lawre...@dal.ca
Date: Saturday, November 7, 2009 6:38 pm
Subject: [R] EM algorithm to fit circular mix of uniform+Von Mises
To: r-h...@stat.math.ethz.ch
Hi all,
I'm curious if anyone has coded an Expectation-Maximization algorithm
that could help me model some circular data I have. I'd like to model
it as a mixture of uniform and Von Mises centered on 0, so the only
free parameters is the mixing proportion and the kappa of the Von
Mises. I couldn't find anything in the contributed packages that
seemed to suit this purpose. Any pointers would be greatly
appreciated!
Cheers,
Mike
--
Mike Lawrence
Graduate Student
Department of Psychology
Dalhousie University
Looking to arrange a meeting? Check my public calendar:
~ Certainty is folly... I think. ~
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