How to compare parameters of non linear fitting curves

Hi,

I'm using a non linear model to fit experimental survival curves.

This model describes the fraction of "still active" experiments as a 
function of time t as follows:
f(t)=(1+exp(-etaD*cD)) / (1+exp(etaD(t-cD)))

Moreover, when experiments are still active, they may change of state 
(from 0 to 1). But they may fall inactive before changing their state 
(their state still equals 0). The survival curve of state may also be 
fitted with the following model:
f(A)=(1+exp(-eta1*c1)) / (1+exp(eta1(t-c1))) * (1+exp(-etaD*cD)) / 
(1+exp(etaD(t-cD)))

I estimate with nlm 1?) values of etaD and cD parameters and 2?) 
inject them as constant in the function to be minimized by nlm to 
estimate values of eta1 and c1.

I perform these estimations for two different experimental conditions 
that both have their values of etaD,eta1, cD and c1.

I would like to know if there is any statistical method to compare the 
estimated values of parameters of the two distributions ? And wether 
it's the case, how to perform it in R ?

Hope I'm clear enough for getting help,

Etienne

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Etienne Toffin, PhD Student
Unit of Social Ecology
Universit? Libre de Bruxelles, CP 231
Boulevard du Triomphe
B-1050 Brussels
Belgium

Tel: +32(0)2/650.55.30
Fax: +32(0)2/650.57.67
http://www.ulb.ac.be/sciences/use/toffin.html