Skip to main content
Article thumbnail
Location of Repository

An R Package for Dynamic Linear Models

By Giovanni Petris


We describe an R package focused on Bayesian analysis of dynamic linear models. The main features of the package are its flexibility to deal with a variety of constant or time-varying, univariate or multivariate models, and the numerically stable singular value decomposition-based algorithms used for filtering and smoothing. In addition to the examples of "out-of-the-box" use, we illustrate how the package can be used in advanced applications to implement a Gibbs sampler for a user-specified model.

OAI identifier:

Suggested articles


  1. (2001). A Primer on Markov Chain Monte Carlo."
  2. (1995). Adaptive Rejection Metropolis Sampling within Gibbs Sampling."
  3. (1997). Bayesian Forecasting and Dynamic Models. 2nd edition.
  4. (2009). Brief User's Guide: Dynamic Systems Estimation (dse). R package version 2009.10-2, URL
  5. (2010). Core Team
  6. (1994). Data Augmentation and Dynamic Linear Models."
  7. (2010). dlm: Bayesian and Likelihood Analysis of Dynamic Linear Models. R package version 1.1-1, URL An R Package for Dynamic Linear Models Petris
  8. (1996). Fixed-Interval Smoothing Algorithm Based on Singular Value Decomposition."
  9. (1989). Forecasting, Structural Time Series Models and the Kalman Filter.
  10. (2006). Formulating State Space Models in R with Focus on Longitudinal Regression Models."
  11. (1992). Kalman Filter Algorithm Based on Singular Value Decomposition."
  12. (1995). Marine Surface Temperature: Observed Variations and Data Requirements."
  13. (2005). Modeling Financial Time Series with S-PLUS. 2nd edition.
  14. (1989). Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms. Cours de Troisi eme Cycle de la Physique en Suisse Romande.
  15. (1994). On Gibbs Sampling for State Space Models."
  16. (1994). Partial Non-Gaussian State Space Models."
  17. (2010). State Space Modeling and Estimation
  18. (1994). Surface Air Temperature Variations: A Reanalysis and Update to 1993."
  19. (2006). Time Series Analysis and Its Applications, with R Examples. 2nd edition.
  20. (1996). Unconstrained Parametrizations for Variance-Covariance Matrices."

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.