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Re: st: RE: RE: RE: generalized nonlinear models
From
Steven Samuels <[email protected]>
To
[email protected]
Subject
Re: st: RE: RE: RE: generalized nonlinear models
Date
Mon, 8 Nov 2010 14:22:51 -0500
--
Perhaps David could use -nl- after all. For computing the MLEs, -nl-
lacks only the the ability to take an analytic weight that is a
function of the parameters (Charnes, Frome, Yu (1976). The equivalence
of generalized least squares and maximum likelihood in the exponential
family, JASA 71:169-171. http://www.csm.ornl.gov/~frome/
JASAIWLS.pdf). One could add this ability in a program that
alternates between an -nl- step with the -log4- option and a step that
updates the analytic weight with the last parameter estimates.
Steve
On Nov 8, 2010, at 1:27 PM, Feiveson, Alan H. (JSC-SK311) wrote:
But -nl- optimizes by least squares, not by maximizing a Poisson (for
example) likelihood. I think David's problem can be addressed by
linearizing the response function in with respct to the parmameters
and then use iterated Poisson regression. Of course to implement this,
you'd have to calculate the first-order linear terms and also have a
way to get first guesses of the nonlinear parameter(s).
Al
-----Original Message-----
From: [email protected] [mailto:[email protected]
] On Behalf Of Nick Cox
Sent: Monday, November 08, 2010 11:50 AM
To: '[email protected]'
Subject: st: RE: RE: generalized nonlinear models
Unless SAS and R have wired-in functions for your model, using -nl- in
Stata strikes me as involving no more programming than using the
equivalents in other languages.
Nick
[email protected]
Airey, David C
Thanks, Stas and Al.
Because the parameters of the 4 parameter logistic function used in
dose-response analysis of drugs and chemicals on biological systems
are the estimation goal, fitting that nonlinear function is desired.
This leaves me with these options
SAS PROC NLMIXED
R gnm package
Programming Stata
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