Discussion Questions

  • What defines a state space model?
  • What is the difference between process and observation error?
  • What are the advantages of modeling them separately?
  • What is the benefit of making predictions of the underlying state even if we can’t observe it?
  • What are some of the complexities that can be incorporated into state space models?
  • How is the normal dynamic linear model constructed?
  • How is nonlinearity integrated?
  • Why is fitting state space models challenging?
  • How might these models be useful for modeling time-series and making forecasts in ecology