Confirmation of acceptance to the course will be sent immediately after the application deadline.Objective
The objective of the course is to guide participants in developing stock assessment models, explaining the key differences between deterministic processes, stochastic models, Bayesian models, and state-space models.
Model development is demonstrated in two related programming environments:
AD Model Builder (ADMB) and Template Model Builder (TMB). Both environments are designed to meet the requirements posed by typical stock assessment models that are nonlinear, highly parameterized, and may have time-varying parameters.
After going through biomass-dynamic models, parametric age-structured models and MCMC analysis, the focus will be on random effects and finally a State-space Assessment Model (SAM), which is used for several assessments within ICES. This is a full stochastic model that allows selectivity to vary gradually with time, using fewer model parameters than full parametric models.
By the end of the course, the participants will be able to:
In this advanced course, participants are assumed to have a background in applied statistics and statistical computing. Specifically, some experience fitting nonlinear models to data (in stock assessment or elsewhere) and basic programming skills.
Arni Magnusson, Marine Research Institute, IcelandAnders Nielsen, DTU Aqua, Denmark
750 Euros (for ICES member country affiliated participants)
1250 Euros (for non-member country affiliated participants)