Moving beyond noninformative priors: why and how to choose weakly informative priors in Bayesian analyses
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Abstract
Throughout the last two decades, Bayesian statistical methods have proliferated throughout ecology and evolution. Numerous previous references established both philosophical and computational guidelines for implementing Bayesian methods. However, protocols for incorporating prior information, the defining characteristic of Bayesian philosophy, are nearly nonexistent in the ecological literature. Here, I hope to encourage the use of weakly informative priors in ecology and evolution by providing a ‘consumer's guide’ to weakly informative priors. The first section outlines three reasons why ecologists should abandon noninformative priors: 1) common flat priors are not always noninformative, 2) noninformative…
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610
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- 64.81
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1Topics & keywords
Topics
Keywords
- Prior probability
- Frequentist inference
- Bayesian probability
- Computer science
- Bayesian inference
- Machine learning
- Artificial intelligence
- Econometrics
UN Sustainable Development Goals
- Life in Land
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