Gaussian state space models (dynamic linear models)

Annual DECIDE workshop 2022

September 26-30 at University of Copenhagen
Focus of the workshop

In 2022, focus will be on Gaussian state space models - i.e. where data is assumed to follow a (possibly multivariate) normal distribution. In those cases where the equations are linear, these models are referred to as Dynamic Linear Models (DLMs).

In order to work with DLMs at an advanced level, a good understanding of linear algebra is required. In case of multivariate models, also knowledge of the multivariate normal distribution is needed. In order to make sure that all participants have the necessary understanding of these topics, brush-up sessions are included in the workshop. 

It is strongly recommended that participants bring own time series data with them to the workshop. During the week, there will be time allocated to work with own data. For those who are not able to bring own data, a data set will be provided. At the end of the workshop, participants present the results of their own analyses. 

Preliminary list of topics covered in 2022
  • Linear algebra, brush up
  • DLM, basic concepts
  • First order univariate DLMs
  • Estimation of variance components
  • Univariate DLM with linear trend component
  • Univariate DLM with Spline function
  • Modeling seasonal or diurnal patterns: Harmonic waves 
  • Introduction to multivariate DLMs
  • Early warning systems based on DLMs
Preliminary time schedule

A preliminary detailed program for the event is available.

Lecturers and instructors

Leonardo Victor de Knegt, Assistant professor
Dan Børge Jensen, Associate professor
Anders Ringgaard Kristensen, Professor

Registration

Send an e-mail to ark@sund.ku.dk (Anders Ringgaard Kristensen) and provide the following information:

  • Name
  • Title
  • Affiliation
  • Role in DECIDE 
  • A short description of your own data

The number of participants is limited to 20. Members of the DECIDE project group have priority but others may attend if there is room.

Literature

A (the) classical introduction to the field is the book by West & Harrison:

West, M. & J. Harrison. 1997. Bayesian Forecasting and Dynamic Models. 2nd Edition. Springer Series in Statistics. Springer, New York.

In the workshop we will use our own textbook notes:

Kristensen, A.R., E. Jørgensen & N. Toft. 2010. Herd Management Science. II. Advanced topics. Academic Books, Copenhagen. ISBN: 9788763461214. 

The textbook will be supplemented with selected articles illustrating the methods discussed. A very brief overview of basic probability theory and distributions may be found in Appendix A of Volume I of Herd Management Science.

Software

The workshop will be based entirely on R and we use the RStudio graphical interface for R. All participants are expected to have both software systems installed. The workshop does not include any formal introduction to R. It is just used as a tool.

Practical information

A separate page provides practical information about transportation, meals and accommodation.