An R Package for Dynamic Linear Models

Giovanni Petris

Journal of Statistical Software, 2010, vol. 036, issue i12

Abstract: 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.

Date: 2010-10-13
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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:036:i12

DOI: 10.18637/jss.v036.i12

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