Dear Statalist,
Is there any reason the "ml" iterative maximization engine could not be
used to maximize functions other than likelihood functions? If, for
instance, one wanted to iteratively choose values for parameters that
maximize a utility or profit function, could one use "ml" or is there
something in the implementation of "ml" that makes it unsuitable for use
with functions that do not have some properties of likelihood functions? I
have read the book "Maximum Likelihood Estimation with Stata, 2d
Edition." I also have read the help file at
http://www.stata.com/stb/stb38/sg71/amoeba.hlp, but do not know if or why
"ml" is unsuitable for general function maximization.
Thank you,
Daniel Lawson
Ph.D. Candidate,
University of Notre Dame
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