IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v201y2010i3p791-798.html
   My bibliography  Save this article

On the link between Markovian trees and tree-structured Markov chains

Author

Listed:
  • Hautphenne, Sophie
  • Houdt, Benny Van

Abstract

In this paper, we describe a link between Markovian binary trees (MBT) and tree-like quasi-birth-and-death processes (TLQBD) by associating a specific TLQBD to each MBT. The algorithms to compute the matrices Gk in the TLQBD then correspond to the algorithms calculating the extinction probability vector of the MBT. This parallelism leads to a new quadratic algorithm, based on the Newton iteration method, which converges to the extinction probability of an MBT. We also present a one-to-one correspondence between a general Markovian tree (GMT) and a scalar tree-structured M/G/1-type Markov chain. This allows us to prove the equivalence between the main result on the positive recurrence, null recurrence or transience of a scalar tree-structured M/G/1-type Markov chain and the criticality of a GMT.

Suggested Citation

  • Hautphenne, Sophie & Houdt, Benny Van, 2010. "On the link between Markovian trees and tree-structured Markov chains," European Journal of Operational Research, Elsevier, vol. 201(3), pages 791-798, March.
  • Handle: RePEc:eee:ejores:v:201:y:2010:i:3:p:791-798
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(09)00228-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nigel Bean & Nectarios Kontoleon & Peter Taylor, 2008. "Markovian trees: properties and algorithms," Annals of Operations Research, Springer, vol. 160(1), pages 31-50, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marco Bonomelli & Rosella Giacometti & Sergio Ortobelli Lozza, 2020. "Joint tails impact in stochastic volatility portfolio selection models," Annals of Operations Research, Springer, vol. 292(2), pages 833-848, September.
    2. Sophie Hautphenne & Guy Latouche & Marie-Ange Remiche, 2011. "Algorithmic Approach to the Extinction Probability of Branching Processes," Methodology and Computing in Applied Probability, Springer, vol. 13(1), pages 171-192, March.

    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:eee:ejores:v:201:y:2010:i:3:p:791-798. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.