rpy2 nls initial parameters choice
Question: Hi I am running a code in python importing rpy2 robjects and trying to make a
fit to some data (with errors that I consider as weights). I am using a non
linear regression and the "formula" i am trying to fit is:
A/((x/t1)^b+(x/t1)^c)

Unfortunately every time I try to run the code I got the usual singular
gradient error:

rpy2.rinterface.RRuntimeError: Error in function (formula, data =
parent.frame(), start, control = nls.control(), : singular gradient

I think is due to my initial value for the parameters (A,t1,b and c). Is there
any way I can have a better guess for the initial values instead just try-
outs? Thanks, nino


Answer: have you checked nlstools in R
<http://cran.r-project.org/web/packages/nlstools/>

