Re: [R] custom loss function + nonlinear models

From: Kjetil Brinchmann Halvorsen <>
Date: Tue 05 Apr 2005 - 07:29:05 EST

Christian Mora wrote:

>Hi all;
>I'm trying to fit a reparameterization of the
>assymptotic regression model as that shown in
>Ratkowsky (1990) page 96.
>where y1,y2,y3 are expected-values for X=x1, X=x2, and
>X=average(x1,x2), respectively.
>I tried first with Statistica v7 by LS and
>Gauss-Newton algorithm without success (no
>convergence: predictors are redundant....). Then I
>tried with the option CUSTOM LOSS FUNCTION and several
>algorithms like Quasi-Newton, Simplex, Hookes-Jeeves,
>among others. In all these cases the model converged
>to some values for the parameters in it.
>My question is (after searching the help pages) : Is
>there such a thing implemented in R or can it be
>easily implemented? In other words, is it possible to
>define which loss function to use and the algorithm to
>find the parameters estimates?
> mailing list
>PLEASE do read the posting guide!
try directly with optim()



Kjetil Halvorsen.

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Received on Tue Apr 05 07:38:58 2005

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