Re: [R] non-linear model parameterization

2007-09-30 Thread Moshe Olshansky
Hi Irene, In this case the computer is right - your gradient is really singular! If you scale all you parameters (g,a and b) by any nonzero constant c nothing changes, meaning that there is a "degree of freedom" and this causes the gradient to be singular. You can check whether g = 0 (and then y =

Re: [R] non-linear model parameterization

2007-09-30 Thread Gabor Grothendieck
The model is not identifiable since if (a, b, g) is a solution then so is every multiple of it. On 9/30/07, Irene Mantzouni <[EMAIL PROTECTED]> wrote: > Dear all, > > I would like to fit a non-linear model of the form: > y=g*x/(a+b*x) > with nls(). > However this model is somehow overparameterized

[R] non-linear model parameterization

2007-09-30 Thread Irene Mantzouni
Dear all, I would like to fit a non-linear model of the form: y=g*x/(a+b*x) with nls(). However this model is somehow overparameterized and I get the error message about singular gradient matrix at initial parameter estimates. What I am interested in is to make inference about parameters b and g