Predictive Efficiency for Simple Non-linear Models*
نویسندگان
چکیده
This paper demonstrates the use of exact predictive likelihood functions for simple non-linear models. A measure of predictive efficiency based on the concept of expected information loss is introduced as a way of comparing alternative prediction functions. It is shown that the predictive likelihood function minimizes expected information loss over a wide class of potential prediction functions. Some Monte Carlo experiments illustrate the performance of alternative prediction functions in settings where prediction is difficult.
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