R help - Feb 2009 - Optimizing Multiple Models...any suggestions?

There are multiple marketing models in place to predict individual-level
probabilities of whether or not someone would respond to a solicitation,
whether or not they would become a customer, and if they did become a
customer, how much money the company is likely to make.  Each individual
receives a score from each model, and the final goal is to rank all
individuals based on a final score.  As long as multiple models exist, I'm
guessing the method of deriving a final score from multiple model scores is
an optimization algorithm.

I have no experience with optimization in R, and was wondering if anyone
could recommend a package or function, or any other method, for this
particular type of problem.  Thanks.
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See:

http://cran.r-project.org/web/views/Optimization.html

On Thu, Feb 12, 2009 at 11:31 AM, Paul Heinrich Dietrich
<paul.heinrich.dietrich at gmail.com> wrote:
>
> There are multiple marketing models in place to predict individual-level
> probabilities of whether or not someone would respond to a solicitation,
> whether or not they would become a customer, and if they did become a
> customer, how much money the company is likely to make.  Each individual
> receives a score from each model, and the final goal is to rank all
> individuals based on a final score.  As long as multiple models exist,
I'm
> guessing the method of deriving a final score from multiple model scores is
> an optimization algorithm.
>
> I have no experience with optimization in R, and was wondering if anyone
> could recommend a package or function, or any other method, for this
> particular type of problem.  Thanks.
> --
> View this message in context:
http://www.nabble.com/Optimizing-Multiple-Models...any-suggestions--tp21979556p21979556.html
> Sent from the R help mailing list archive at Nabble.com.
>
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