Common criteria to judge competing models to be used in passive prediction include:
A) degree of exogenous variation.
B) model fit.
C) data mining.
D) pattern discovery.

Question

Quizplus · Accepted Answer

Model fit is the most important criteria when judging competing models for passive prediction. It measures how well the model is able to fit the observed data and make accurate predictions. The other options, such as degree of exogenous variation, data mining, and pattern discovery, may also be important but are not as essential as model fit.

Common Criteria to Judge Competing Models to Be Used in Passive