title: rpy2 nls initial parameters choice
body: <p>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)</p>
  
  <p>Unfortunately every time I try to run the code I got the usual singular gradient error:</p>
  
  <p>rpy2.rinterface.RRuntimeError: Error in function (formula, data = parent.frame(), start, control = nls.control(),  : 
    singular gradient</p>
  
  <p>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 </p>