IDEAS home Printed from https://ideas.repec.org/a/ibn/ijspjl/v13y2025i1p10.html
   My bibliography  Save this article

Estimating and Calibrating Markov Chain Sample Error Variance

Author

Listed:
  • Yann Vestring
  • Javad Tavakoli

Abstract

Markov chain Monte Carlo (MCMC) methods are a powerful and versatile tool with applications spanning a wide spectrum of fields, including Bayesian inference, computational biology, and physics. One of the key challenges in applying MCMC algorithms is to deal with estimation error. The main result in this article is a closed form, non-asymptotic solution for the sample error variance of a single MCMC estimate. Importantly, this result assumes that the state-space is finite and discrete. We demonstrate with examples how this result can help estimate and calibrate MCMC estimation error variance in the more general case, when the state-space is continuous and/or unbounded.

Suggested Citation

  • Yann Vestring & Javad Tavakoli, 2025. "Estimating and Calibrating Markov Chain Sample Error Variance," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 13(1), pages 1-10, January.
    • Handle: RePEc:ibn:ijspjl:v:13:y:2025:i:1:p:10
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/ijsp/article/download/0/0/49902/53961
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/ijsp/article/view/0/49902
    Download Restriction: no
    ---><---

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:ibn:ijspjl:v:13:y:2025:i:1:p:10. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.