Why Model Averaging?

  • David FletcherEmail author
Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)


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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© The Author(s), under exclusive licence to Springer-Verlag GmbH, DE, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mathematics and StatisticsUniversity of OtagoDunedinNew Zealand

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