FISH 509

Bayesian Methods for Fisheries Stock Assessment

Credit Value

3 credits

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. Minimal entry requirement: first year undergraduate calculus and FISH 504.

Assessment

  • 25% Comparing frequentist and Bayesian regression analysis
  • 25% Reparameterizing models to facilitate Bayesian parameter estimation
  • 25% Bayesian hierarchical modeling
  • 25% Bayesian mark-recapture modeling

Course Organizer

Dr Murdoch McAllister