IDEAS home Printed from https://ideas.repec.org/a/jss/jstsof/v036i12.html
   My bibliography  Save this article

An R Package for Dynamic Linear Models

Author

Listed:
  • Petris, Giovanni

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.

Suggested Citation

  • Petris, Giovanni, 2010. "An R Package for Dynamic Linear Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i12).
    • Handle: RePEc:jss:jstsof:v:036:i12
    DOI: http://hdl.handle.net/10.18637/jss.v036.i12
    as

    Download full text from publisher

    File URL: https://www.jstatsoft.org/index.php/jss/article/view/v036i12/v36i12.pdf
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v036i12/dlm_1.1-2.tar.gz
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v036i12/v36i12.R
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v036i12/dlmGibbsDIGt.R
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v036i12/Folland.dat
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v036i12/HL.dat
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v036i12/IPCONGD.txt
    Download Restriction: no
    File URL: https://libkey.io/http://hdl.handle.net/10.18637/jss.v036.i12?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cabral, Celso Rômulo Barbosa & da-Silva, Cibele Queiroz & Migon, Helio S., 2014. "A dynamic linear model with extended skew-normal for the initial distribution of the state parameter," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 64-80.
    2. Shao, Wei & Guo, Guangbao & Meng, Fanyu & Jia, Shuqin, 2013. "An efficient proposal distribution for Metropolis–Hastings using a B-splines technique," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 465-478.
    3. Sun, He, 2023. "Deep Learning and Bayesian Calibration Approach to Hourly Passenger Occupancy Prediction in Beijing Metro: A Study Exploiting Cellular Data and Metro Conditions," DES - Working Papers. Statistics and Econometrics. WS 38783, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Reusens Peter & Croux Christophe, 2017. "Detecting time variation in the price puzzle: a less informative prior choice for time varying parameter VAR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
    5. Schütz, Peter & Westgaard, Sjur, 2018. "Optimal hedging strategies for salmon producers," Journal of Commodity Markets, Elsevier, vol. 12(C), pages 60-70.
    6. Ekici, Oya & Nemlioğlu, Karun, 2017. "Emerging economies’ short-term private external debt as evidence of economic crisis," Journal of Policy Modeling, Elsevier, vol. 39(2), pages 232-246.
    7. Peter Knaus & Angela Bitto-Nemling & Annalisa Cadonna & Sylvia Fruhwirth-Schnatter, 2019. "Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP," Papers 1907.07065, arXiv.org, revised Nov 2020.
    8. Kleyton da Costa & Felipe Leite Coelho da Silva & Josiane da Silva Cordeiro Coelho & Andr'e de Melo Modenesi, 2020. "A Systematic Comparison of Forecasting for Gross Domestic Product in an Emergent Economy," Papers 2010.13259, arXiv.org, revised Mar 2022.
    9. Ruiz-Cárdenas, Ramiro & Krainski, Elias T. & Rue, Håvard, 2012. "Direct fitting of dynamic models using integrated nested Laplace approximations — INLA," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1808-1828.
    10. Andrés Ramírez Hassan & Javier Pantoja Robayo, 2013. "Co-movements between Latin American and U.S. stock markets: convergence after the financial crisis," Documentos de Trabajo de Valor Público 10931, Universidad EAFIT.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jss:jstsof:v:036:i12. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum (email available below). General contact details of provider: http://www.jstatsoft.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.