I am a relatively new user of Splus (experienced user of stata)
I would like to use maximum likelihood to fit a model which can be
expressed as a function of a linear predictor:
L= A*(1-p)^2 + B*p*(1-p) + C*p^2
A, B and C are fixed constants, and p=1/(1+exp(-eta)) where eta=Xb.
I have found the function nlmin and can use this to obtain maximum
likelihood estimates of b. However, I would also like to obtain standard
errors and believe asymptotic properties of MLEs may not hold. Therefore
I would like to use clustered robust estimation.
Can anyone point me in the direction of appropriate functions or some
example code? The robust library available in Splus v 6.1 does not appear
to allow user-defined likelihoods.
Many thanks, Chris.
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