IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v22y1995i2p87-96.html
   My bibliography  Save this article

A class of strong laws for functionals of countable nonhomogeneous Markov chains

Author

Listed:
  • Liu, Wen
  • Liu, Guoxin

Abstract

In this paper, we use an analytic approach to study the limit properties of {inn(Xn)}, the functional of a countable nonhomogeneous Markov chain {Xn}. A class of strong laws of large numbers for these processes, which are different from the usual ones, are obtained. In the theorems of this paper, the expectation E(fn(Xn)) in the usual strong laws of large numbers is replaced by the conditional expectation E(fn(Xn(Xn-1)). Some classical strong laws of large numbers for sequences of independent random variables are implied by the results of this paper.

Suggested Citation

  • Liu, Wen & Liu, Guoxin, 1995. "A class of strong laws for functionals of countable nonhomogeneous Markov chains," Statistics & Probability Letters, Elsevier, vol. 22(2), pages 87-96, February.
    • Handle: RePEc:eee:stapro:v:22:y:1995:i:2:p:87-96
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0167-7152(94)00053-B
    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.

    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:stapro:v:22:y:1995:i:2:p:87-96. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.