Are state-space stock assessment model confidence intervals accurate? Case studies with SAM and Barents Sea stocks

• Published in: Fisheries Research
• Main Authors: Cadigan, Noel G., Albertsen, Christoffer Moesgaard, Zheng, Nan, Nielsen, Anders
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2024
• Subjects: State-space model; Bias; Confidence intervals; Random effects; Conditional; Barents Sea
• Online Access: https://orbit.dtu.dk/en/publications/7a66ee11-fd8f-43f9-a4da-820670f8c4b5; https://doi.org/10.1016/j.fishres.2024.106950; https://backend.orbit.dtu.dk/ws/files/349427127/1-s2.0-S0165783624000146-main.pdf

Our main contribution is to examine the reliability of confidence intervals using the SAM state-space fish stock assessment model used for the assessment of many stocks by the International Council for the Exploration of the Seas. We focus on frequentist statistical inferences and more specifically on inference conditioned on specific values of the state-space model random effects drawn from their process distribution. This is somewhat consistent with simulation self-test procedures that are commonly used to examine the reliability of state-space assessment model results. However, recent research has indicated that some estimation bias may be expected in the conditional setting. Hence, we also investigate recently proposed bias corrected confidence intervals appropriate for the conditional inference setting. The SAM simulation coverage probabilities of 95% confidence intervals for SSB and Fbar were usually slightly larger than 95%, but in a small number of years these coverage probabilities could be much smaller than 95%. The bias corrected confidence intervals were more reliable. When averaged over years, the SAM and bias corrected confidence interval coverage probabilities were similar for the Northeast Artic cod and saithe case studies, but the bias corrected confidence intervals performed much better overall for the haddock case study.