Detecting significant retrospective patterns in state space fish stock assessment
Journal article, Peer reviewed
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Original versionCanadian Journal of Fisheries and Aquatic Sciences. 2023, 80 (9), 1509-1518. 10.1139/cjfas-2022-0250
Retrospective patterns are commonly investigated to validate fish stock assessment models. A widely applied measure for retrospective bias is Mohn’s ρ and corresponding retrospective plots. However, retrospective patterns can be interpreted differently by experts. To make decisions regarding significant retrospective patterns less subjective, we proposed a post-sample Mohn’s ρ significance test. As case studies, we applied the state space assessment model SAM with data on Northeast Arctic cod and Norwegian coastal cod north of 67◦N. We showed that the acceptance regions of Mohn’s ρ depends on both the data available and the assessment model complexity. We also assessed the test power under a range of assumption violations and conclude that Mohn’s ρ is useful for detecting violations associated with bias, but not for violations associated with variances and correlations.