Bayesian Methods for Fisheries Stock Assessment |
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| Credit Value: 3 Credits
Schedule: Term 1, 2025 Prerequisites, Restrictions, and Notes: Minimal entry requirement: first-year undergraduate calculus and FISH 504. Description:This course provides an introduction to Bayesian data analysis and statistical modeling methods that are commonly utilized in fisheries stock assessment. Methods covered include approaches that have been applied in fisheries stock assessment to formulate priors, grid-based, importance sampling, and Markov Chain Monte Carlo Methods for integration of posterior distributions for fisheries model parameters, introduction to WinBUGS software for fisheries modeling, diagnostics to assess convergence and goodness of fit, methods to compute Bayes’ posteriors (or factors) for alternative fisheries models, fisheries hierarchical models, and Bayesian mark-recapture methods and state-space population dynamics models for fish stock assessment. Assessment: This course has four graded components, each counting for 25% of the final grade.
Course Instructor: Dr Murdoch McAllister |
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