Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Giovanni Petris
Title: An R Package for Dynamic Linear Models
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.

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Paper: An R Package for Dynamic Linear Models     Download PDF (Downloads: 35703)
Supplements:
dlm_1.1-2.tar.gz: R source package Download (Downloads: 1347; 374KB)
v36i12.R: R example code from the paper Download (Downloads: 2018; 6KB)
dlmGibbsDIGt.R: Supplementary R function Download (Downloads: 1462; 10KB)
Folland.dat: Example data in plain text format Download (Downloads: 1203; 752B)
HL.dat: Example data in plain text format Download (Downloads: 1274; 750B)
IPCONGD.txt: Example data in plain text format Download (Downloads: 1425; 18KB)
DOI: 10.18637/jss.v036.i12

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.