Re: [R] Hypothesis testing after optim

[Spencer Graves]

For nested models, 2*log(likelihood ratio) is approximately chi-square 
with degrees of freedom = the number of parameters estimated for the 
larger model that were not in the smaller model minus any additional 
constraints.  You can compute 2*log(likelihood ratio) as twice the 
difference in the log(likelihoods) at the optimum and then use pchisq to 
conver that to a significance probability.

hope this helps.  spencer graves

Peter Muhlberger wrote:
Hi folks:  Does anyone know of a way to do (linear) hypothesis tests of
parameters after fitting a maximum-likelihood model w/ optim?  I can't seem
to find anything like a Wald test whose documentation says it applies to
optim output.  

Also, thanks again to everyone who gave me feedback on the robustness of ML
estimation in R!
Peter

********************************
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Peter Muhlberger
Visiting Professor of Political Science
Institute for the Study of Information Technology and Society (InSITeS)
Carnegie Mellon University
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