Impacts of prior mis-specification on Bayesian fisheries stock assessment
Resource
Marine and Freshwater Research 59: 145-156
Journal
Marine and Freshwater Research
Pages
145
Date Issued
2008
Date
2008
Author(s)
Chen, Yong
Sun, Chi-Lu
Kanaiwa, Minoru
Abstract
One of the key features of a Bayesian stock assessment is that the modeller needs to provide knowledge on model parameters. Priors summarise modellers' understanding of model parameters and are often defined by a probability distribution function. Priors are often mis-specified with arbitrary and unrealistic accuracy and precision in perceiving the state of nature for the parameters as a result of our limited understanding of fisheries ecosystems. Commonly used probability functions such as normal distribution functions tend to be sensitive to prior mis-specification, resulting in large uncertainty and/or errors in Bayesian stock assessment. Fat-tailed functions such as the Cauchy distribution function have been found to be robust to prior mis-specification. Using the Maine sea urchin fishery as an example, we evaluated the impacts of mis-specification in defining the prior distributions on Bayesian stock assessment. The present study suggests that the quantification of priors with a Cauchy distribution tends to be robust to the prior mis-specification. Given our limited understanding of fisheries a function such as the Cauchy distribution function that is robust to prior mis-specification tends to be more desirable. Future studies should explore the use of other fat-tailed distribution functions for quantifying priors in fisheries stock assessment. © CSIRO 2008.
Subjects
Bayesian stock assessment; Cauchy distribution; Prior; Prior mis-specification; Robust; Uncertainty
SDGs
Other Subjects
Bayesian analysis; echinoderm; ecological modeling; marine ecosystem; stock assessment; uncertainty analysis; Echinoidea
Type
journal article
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