Class material: webpage

This week, we discuss issues related to the estimation of the B matrix in the context of using it to represent species interactions in a community dynamics models.

* univariate discrete time Gompertz model

* multivariate discrete time Gompertz model

* including covariates

* spurious density dependence resulting from ignoring observation error

* uncertainty in B elements resulting from estimating observation variance

* different methods for estimating confidence intervals: bootstrapping, hessian approximation, profile likelihood

* diagnostics

The main lab is to go through case study 7 in the MARSS User Guide and the corresponding code.

You can find the pdf of lecture on the class webpage.

**Week 8: Estimating interactions (the B matrix)**This week, we discuss issues related to the estimation of the B matrix in the context of using it to represent species interactions in a community dynamics models.

* univariate discrete time Gompertz model

* multivariate discrete time Gompertz model

* including covariates

* spurious density dependence resulting from ignoring observation error

* uncertainty in B elements resulting from estimating observation variance

* different methods for estimating confidence intervals: bootstrapping, hessian approximation, profile likelihood

* diagnostics

**Lab 8**The main lab is to go through case study 7 in the MARSS User Guide and the corresponding code.

**Lecture 8**You can find the pdf of lecture on the class webpage.