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st: RE: RE: RE: RE: generalized nonlinear models


From   Nick Cox <[email protected]>
To   "'[email protected]'" <[email protected]>
Subject   st: RE: RE: RE: RE: generalized nonlinear models
Date   Mon, 8 Nov 2010 18:30:42 +0000

If the SAS and R routines both use ML, then indeed I am wrong. 

Nick 
[email protected] 


-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Feiveson, Alan H. (JSC-SK311)
Sent: 08 November 2010 18:27
To: [email protected]
Subject: st: RE: RE: RE: generalized nonlinear models

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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