Look at optim, or mle in package stats4.

There are a lot of similar problems addressed in R: few real-world likelihoods have `an explicit formula'. One quite similar example is ARIMA fitting.

On Thu, 19 Jan 2006, Dominik Heinzmann wrote:

Dear R-users

Problem:

Given the following system of ordinary differential euqations

dM/dt = (-n)*M-h*M
dS/dt = n*M-h*S+u*R
dA/dt = h*S-q*A
dI/dt = q*A-p*I
dJ/dt = h*M-v*J
dR/dt=p*I+v*J-u*R

where M,S,A,I,J,R are state variables and n,h,u,q,p,v parameters.

I'm able to calculate the likelihood value based on the solutions
M,S,A,I,J,R of the ODE's given the data, but without an explicit formula.

How can I now optimize the loglikelihood with respect to the parameter
n,h,u,q,p,v? Is there any functions available in R for dealing with such
empirical likelihood problems?

Thanks a lot for your support.

--
Dominik Heinzmann
Master of Science in Mathematics, EPFL
Ph.D. student in Biostatistics
Institute of Mathematics
University of Zurich

Winterthurerstrasse 190
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Office: Y36L90

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Homepage: http://www.math.unizh.ch/user/heinzmann

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--
Brian D. Ripley,                  [EMAIL PROTECTED]
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
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