[R] Poor performance of "Optim"

[yehengxin]

What I tried is just a simple binary probit model.   Create a random data and
use "optim" to maximize the log-likelihood function to estimate the
coefficients.   (e.g. u = 0.1+0.2*x + e, e is standard normal.  And y = (u >
0),  y indicating a binary choice variable)

If I estimate coefficient of "x", I should be able to get a value close to
0.2 if sample is large enough.  Say I got 0.18. 

If I expand x by twice and reestimate the model, which coefficient should I
get?  0.09, right?

But with "optim", I got something different.  When I do the same thing in
both Gauss and Matlab, I can exactly get 0.09, evidencing that the
coefficient estimator is reliable.  But R's "optim" does not give me a
reliable estimator. 

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