IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v28y2007i5p744-762.html
   My bibliography  Save this article

On Bayesian analysis of nonlinear continuous‐time autoregression models

Author

Listed:
  • O. Stramer
  • G. O. Roberts

Abstract

. This article introduces a method for performing fully Bayesian inference for nonlinear conditional autoregressive continuous‐time models, based on a finite skeleton of observations. Our approach uses Markov chain Monte Carlo and involves imputing data from times at which observations are not made. It uses a reparameterization technique for the missing data, and because of the non‐Markovian nature of the models, it is necessary to adopt an overlapping blocks scheme for sequentially updating segments of missing data. We illustrate the methodology using both simulated data and a data set from the S & P 500 index.

Suggested Citation

  • O. Stramer & G. O. Roberts, 2007. "On Bayesian analysis of nonlinear continuous‐time autoregression models," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(5), pages 744-762, September.
    • Handle: RePEc:bla:jtsera:v:28:y:2007:i:5:p:744-762
    DOI: 10.1111/j.1467-9892.2007.00549.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9892.2007.00549.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9892.2007.00549.x?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. Su, Fei & Chan, Kung-Sik, 2015. "Quasi-likelihood estimation of a threshold diffusion process," Journal of Econometrics, Elsevier, vol. 189(2), pages 473-484.

    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:bla:jtsera:v:28:y:2007:i:5:p:744-762. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.