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<SPAN
>[HB] If I look at the
list of alternative models sorted according to my objective function and decide,
for some reason, that I prefer one other that the one at the top of the list,
then I have not included something important in the definition of my objective
function. I need to revise my objective function, and rerun earlier test
runs and model selections.
<SPAN
>
<SPAN
>[AV] Howard, I can
envision one reason for rejecting the top parameter value or model of an
objective function without resorting to the need to improve the definition of
the objective function. Suppose, as an example, your objective function were
simply net % profit, which AB's opt currently sorts on. Suppose the net% profit
in the top model were 100%. Then, looking at the next 3 or 4 models just below
the top, suppose the net % profit were 85.14, 84.26, 83.89, and 81.99. I would
choose one of the next 3 rather than the top one because choosing the top one
imposes a non-robustness to your system results, a local optimum that may have
occurred by chance. Changing a parameter just a small bit changes the
profitability by 15%, whereas changing that same parameter by the same amount
from there only changes profitability a few tenths of a percent. So, the system
is more robust in that area of 2- or 3-dimensional space than the top
one.
<SPAN
>
<SPAN
>Al
Venosa
<SPAN
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