IDEAS home Printed from https://ideas.repec.org/a/spr/mathme/v65y2007i2p353-360.html
   My bibliography  Save this article

Analysis on adjoint non-recurrent property of nonlinear time series in random environment domain

Author

Listed:
  • Enwen Zhu
  • Jiezhong Zou
  • Zhenting Hou

Abstract

By introducing a random interference into the typical of nonlinear time series model, this paper establishes a RENLAR model: $$X_{n+1}=T(X_n)+ e_{n+1}(Z_{n+1})$$ . The author introduces the definition of adjoint non-recurrence, and utilizing general state space Markov chain theorem, we obtain some criteria for non-recurrence and adjoint non-recurrence of nonlinear time series models in random environment domain and analyze adjoint non-recurrence of some models by using these criteria. Copyright Springer-Verlag 2007

Suggested Citation

  • Enwen Zhu & Jiezhong Zou & Zhenting Hou, 2007. "Analysis on adjoint non-recurrent property of nonlinear time series in random environment domain," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 65(2), pages 353-360, April.
    • Handle: RePEc:spr:mathme:v:65:y:2007:i:2:p:353-360
    DOI: 10.1007/s00186-006-0128-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00186-006-0128-7
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00186-006-0128-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Bhattacharya, Rabi & Lee, Chanho, 1995. "On geometric ergodicity of nonlinear autoregressive models," Statistics & Probability Letters, Elsevier, vol. 22(4), pages 311-315, March.
    2. Zhenting Hou & Zheng Yu & Peng Shi, 2005. "Study on a class of nonlinear time series models and ergodicity in random environment domain," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 61(2), pages 299-310, June.
    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. Mika Meitz & Pentti Saikkonen, 2008. "Stability of nonlinear AR‐GARCH models," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(3), pages 453-475, May.
    2. Rydlewski, Jerzy P. & Snarska, Małgorzata, 2014. "On geometric ergodicity of skewed—SVCHARME models," Statistics & Probability Letters, Elsevier, vol. 84(C), pages 192-197.
    3. repec:lan:wpaper:2374 is not listed on IDEAS
    4. Andrews, Donald W.K. & Cheng, Xu, 2013. "Maximum likelihood estimation and uniform inference with sporadic identification failure," Journal of Econometrics, Elsevier, vol. 173(1), pages 36-56.
    5. Hernández-Lerma, Onésimo & Lasserre, Jean B., 1996. "Existence of bounded invariant probability densities for Markov chains," Statistics & Probability Letters, Elsevier, vol. 28(4), pages 359-366, August.
    6. repec:lan:wpaper:2372 is not listed on IDEAS
    7. Isao Ishida & Virmantas Kvedaras, 2015. "Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity," Econometrics, MDPI, vol. 3(1), pages 1-53, January.
    8. Jean‐Pierre Stockis & Jürgen Franke & Joseph Tadjuidje Kamgaing, 2010. "On geometric ergodicity of CHARME models," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(3), pages 141-152, May.
    9. Felix Chan & Michael McAleer & Marcelo C. Medeiros, 2015. "Structure and asymptotic theory for nonlinear models with GARCH erros," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 16(1), pages 1-21.
    10. Carrasco, Marine, 2002. "Misspecified Structural Change, Threshold, and Markov-switching models," Journal of Econometrics, Elsevier, vol. 109(2), pages 239-273, August.
    11. Arash Nademi & Rahman Farnoosh, 2014. "Mixtures of autoregressive-autoregressive conditionally heteroscedastic models: semi-parametric approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(2), pages 275-293, February.
    12. Lu, Zudi & Jiang, Zhenyu, 2001. "L1 geometric ergodicity of a multivariate nonlinear AR model with an ARCH term," Statistics & Probability Letters, Elsevier, vol. 51(2), pages 121-130, January.
    13. An, H. Z. & Chen, S. G., 1997. "A note on the ergodicity of non-linear autoregressive model," Statistics & Probability Letters, Elsevier, vol. 34(4), pages 365-372, June.
    14. Eckhard Liebscher, 2005. "Towards a Unified Approach for Proving Geometric Ergodicity and Mixing Properties of Nonlinear Autoregressive Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(5), pages 669-689, September.
    15. Lee, Oesook & Shin, Dong Wan, 2000. "On geometric ergodicity of the MTAR process," Statistics & Probability Letters, Elsevier, vol. 48(3), pages 229-237, July.
    16. Michael Vogt, 2012. "Nonparametric regression for locally stationary time series," CeMMAP working papers CWP22/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. S. Valère Bitseki Penda & Adélaïde Olivier, 2017. "Autoregressive functions estimation in nonlinear bifurcating autoregressive models," Statistical Inference for Stochastic Processes, Springer, vol. 20(2), pages 179-210, July.
    18. I A Venetis & I Paya & D Peel, 2009. "ESTAR model with multiple fixed points. Testing and Estimation," Working Papers 599093, Lancaster University Management School, Economics Department.
    19. repec:lan:wpaper:2453 is not listed on IDEAS
    20. Lee, Oesook, 2000. "On probabilistic properties of nonlinear ARMA(p,q) models," Statistics & Probability Letters, Elsevier, vol. 46(2), pages 121-131, January.
    21. Müller, Ursula U. & Schick, Anton & Wefelmeyer, Wolfgang, 2009. "Estimators for alternating nonlinear autoregression," Journal of Multivariate Analysis, Elsevier, vol. 100(2), pages 266-277, February.
    22. Joseph Tadjuidje Kamgaing & Hernando Ombao & Richard A. Davis, 2009. "Autoregressive processes with data‐driven regime switching," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(5), pages 505-533, September.
    23. repec:lan:wpaper:2595 is not listed on IDEAS
    24. Lee, Chanho, 1998. "Asymptotics of a class of pth-order nonlinear autoregressive processes," Statistics & Probability Letters, Elsevier, vol. 40(2), pages 171-177, September.

    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:spr:mathme:v:65:y:2007:i:2:p:353-360. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.