[ADMB Users] restricted maximum likelihood

[Mark Maunder]

Ian,

I think that the procedure that you describe is a computational
convenience, just like similar two step procedures used to calculate
random effect models.

Mark


 
Mark Maunder 
Head of the Stock Assessment Program
Inter-American  Tropical Tuna Commission
8604 La Jolla Shores Drive
La Jolla, CA, 92037-1508, USA
  
Tel: (858) 546-7027
Fax: (858) 546-7133
mmaunder at iattc.org
http://www.fisheriesstockassessment.com/TikiWiki/tiki-index.php?page=Mar
k+Maunder
 
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-----Original Message-----
From: users-bounces at admb-project.org
[mailto:users-bounces at admb-project.org] On Behalf Of Ian Fiske
Sent: Friday, April 16, 2010 7:38 AM
To: users at admb-project.org
Subject: [ADMB Users] restricted maximum likelihood

Hi all,

The ADMB-RE manual briefly discusses implementing restricted maximum
likelihood (REML) estimation.  The suggested approach is to integrate
out the fixed effects by specifying them as a random_effects_vector.
This makes sense.  However, the usual REML practice is to

(1) estimate variance parameters using the integrated likelihood.
(2) estimate fixed effects conditional on the variance estimate from
(1).
(3) iterate between (1) and (2) for nonlinear models.

In contrast, the ADMB-RE method estimates fixed effect parameters
using EBLUPs just like random effects.  Does this turn out to be
equivalent to the usual procedure above because no prior is specified
for fixed effects?  I guess the most obvious difference is that fixed
effects and random effects are estimated simultaneously within the
inner minimization.  Does this matter?  Maybe this is obvious, but I
just want to be sure I know what I'm doing.

Thanks!
Ian

-- 
Ian Fiske
PhD Candidate
Department of Statistics
North Carolina State University
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