Week 10: Applied Time-Series Analysis for Fisheries and Environmental Data

Class material: webpage

Week 10: Dynamic linear models
This week, we give a brief introduction to an important class of MARSS models: dynamic linear models. These are multivariate linear regression models where the regression parameters (slope and intercepts) are treated as a AR process and thus are allowed to time evolve. We also review some of the diagnostics for MARSS models fits.

Lab 10 In the lab, you'll go through an simple example of a univariate dynamic linear model with time-varying slope and intercept.
Lecture 10 You can find the pdf of lecture on the class webpage along with the link to watch a recording of the lecture.

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Week 9: Applied Time-Series Analysis for Fisheries and Environmental Data

Class material: webpage

Week 9: Bayesian hierarchical multivariate state-space models
This week, we discuss fitting non-linear MARSS models and MARSS models with non-Gaussian errors using Bayesian methods. This is a very brief introduction and many shows some examples of how one sets up a MARSS model in JAGS and shows you what the posteriors of some models look like.
* Posteriors for MARSS models
* Intro to JAGS (the Gibbs sampler we will be using)
* many examples of fitting non-linear and non-Gaussian MARSS models

Lab 9 The main lab is to go through the JAGS examples shown in the lecture.
Lecture 9 You can find the pdf of lecture on the class webpage along with the link to watch a recording of the lecture.

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