Dear Statalist Users,
I'm trying to write a maximum likelihood estimation code for a probit
model with many endogenous variables. There is an existing procedure,
ivprob, which does this when you have a single endogenous variable (so
errors are assumed bivariate normal) but I'm trying to extend this to a
four-endogenous-variable case. The expressions that go into the likelihood
function are extremely long and messy but this is in principle a
straightforward generalization of the bivariate case so I think it should
work.
My ml program has passed "ml check" and I've searched for initial values
using "ml search" (I'm using the lf method.) However I am running into
numerical difficulties. I keep getting an error message saying
could not calculate numerical derivatives
missing values encountered
I've looked at the value of the log likelihood and I'm getting impossibly
large values. For example, one line I get before the program crashes says
rescale: log likelihood = 6.18e+307
I can check my equations again but they all come from manipulations of
matrices in Mathematica so I doubt my formulas are wrong.
I've searched for this error message in the archive and on google as well
as Gould and Sribney's book (first ed) but have not found much advice on
what to do about it.
I would very much appreciate any advice from other users. Thanks very much
in advance.
Jason Hwang
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