IDEAS home Printed from
   My bibliography  Save this paper

General Autoregressive Modelling of Markov Chains



The reduction of the number of parameters in high-order Markov chain already inspired several articles. In particular, Raftery proposed an autoregressive modelling which utilizes the same transition matrix, with a coefficient, for every lag. In this paper, we show that a model of the same type, but utilizing different matrices, gives best results and is not harder to estimate, even when the number of data is small. A numerical illustration confirms the theoretical results.

Suggested Citation

  • Berchtold, A, 1995. "General Autoregressive Modelling of Markov Chains," Working Papers 95.05, Université de Genè, Theory and Mathematics of the Economy and the Society.
  • Handle: RePEc:wop:tmeswp:9505

    Download full text from publisher

    File URL:
    Download Restriction: no


    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:wop:tmeswp:9505. 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: Thomas Krichel (email available below). General contact details of provider: .

    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.