Testing a linear hypothesis after maximum likelihood

Why can't you use a likelihood ratio?  I would write two slightly 
different functions, the second of which would use the linear constraint 
to eliminate one of the coefficients.  Then I'd refer 2*log(likelihood 
ratio) to chi-square(1).  If I had some question about the chi-square 
approximation to the distribution of that 2*log(likelihood ratio) 
statistic, I'm use some kind of Monte Carlo, e.g., MCMC.

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	  hope this helps.
	  spencer graves

I'd like to be able to test linear hypotheses after setting up and running a
model using optim or perhaps nlm.  One hypothesis I need to test are that
the average of several coefficients is less than zero, so I don't believe I
can use the likelihood ratio test.

I can't seem to find a provision anywhere for testing linear combinations of
coefficients after max. likelihood.

Cheers & happy holidays,

Peter

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Spencer Graves, PhD
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