Why Model Averaging

Model averaging is a means of allowing for model uncertainty in estimation which can provide better estimates and more reliable confidence intervals than model selection. We illustrate its use via examples involving real data, discuss when it is likely to be useful, and compare the frequentist and Bayesian approaches to model averaging.

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