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Technical Note—Mean Drifts and the Non-Ergodicity of Markov Chains

Author

Listed:
  • Linn I. Sennott

    (Illinois State University, Normal, Illinois)

  • Pierre A. Humblet

    (Massachusetts Institute of Technology, Cambridge, Massachusetts)

  • Richard L. Tweedie

    (Siromath Pty., Ltd., Sydney, Australia)

Abstract

An important question in stochastic modeling is whether or not a denumerable state Markov chain is ergodic. We extend a result of Kaplan giving a condition for the non-ergodicity of a chain based on its drifts. We also clarify the condition under which the mean drift in the stationary chain is zero.

Suggested Citation

  • Linn I. Sennott & Pierre A. Humblet & Richard L. Tweedie, 1983. "Technical Note—Mean Drifts and the Non-Ergodicity of Markov Chains," Operations Research, INFORMS, vol. 31(4), pages 783-789, August.
    • Handle: RePEc:inm:oropre:v:31:y:1983:i:4:p:783-789
    DOI: 10.1287/opre.31.4.783
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    Cited by:

    1. D. Arivudainambi & P. Godhandaraman, 2015. "Retrial queueing system with balking, optional service and vacation," Annals of Operations Research, Springer, vol. 229(1), pages 67-84, June.
    2. Wee Meng Yeo & Xue-Ming Yuan & Joyce Mei Wan Low, 2017. "On $$M^{X}/G(M/H)/1$$ M X / G ( M / H ) / 1 retrial system with vacation: service helpline performance measurement," Annals of Operations Research, Springer, vol. 248(1), pages 553-578, January.
    3. Jeongsim Kim & Bara Kim, 2016. "A survey of retrial queueing systems," Annals of Operations Research, Springer, vol. 247(1), pages 3-36, December.
    4. Samira Taleb & Amar Aissani, 2016. "Preventive maintenance in an unreliable M/G/1 retrial queue with persistent and impatient customers," Annals of Operations Research, Springer, vol. 247(1), pages 291-317, December.

    More about this item

    Keywords

    567 mean drifts and non-ergodicity;

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