@article{JSSv036i12, title={An R Package for Dynamic Linear Models}, volume={36}, url={https://www.jstatsoft.org/index.php/jss/article/view/v036i12}, doi={10.18637/jss.v036.i12}, abstract={We describe an <b>R</b> 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.}, number={12}, journal={Journal of Statistical Software}, author={Petris, Giovanni}, year={2010}, pages={1–16} }