Jan,
If your model is y=A/(A+p^r) and p is non-negative
I think that you could solve it using logarithms:
For B=A^(1/r) and x=r*log(p/B) you have
y = 1/(1+(p/B)^r) = 1/(1+exp(r*log(p/B))) = 1/(1+exp(x))
Then for 0<y<1 and z=y/(1-y) you have log(z) = -x
Rodrigo.
----- Original Message -----
From: "Jan Heufer" <[email protected]>
To: <[email protected]>
Sent: Tuesday, November 14, 2006 10:08 PM
Subject: st: Nonlinear Tobit
Hi,
how can I estimate a nonlinear model, when the dependent variable is left- =
and right-censored?
Specifically, I would like to estimate
y =3D A/(A+p^r),
where p is the independent variable, A and r are parameters to be estimated=
, and y is censored at 0 and 1.
I am aware that it is not a problem to estimate the model with NLS, ignorin=
g the censoring. But I'd be really thankful if I could get help on how to u=
se tobit for the model.
Cheers!
--=20
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