IDEAS home Printed from https://ideas.repec.org/a/spr/aistmt/v56y2004i2p225-250.html
   My bibliography  Save this article

Asymptotic distributions of M-estimators in a spatial regression model under some fixed and stochastic spatial sampling designs

Author

Listed:
  • S. Lahiri
  • Kanchan Mukherjee

Abstract

No abstract is available for this item.

Suggested Citation

  • S. Lahiri & Kanchan Mukherjee, 2004. "Asymptotic distributions of M-estimators in a spatial regression model under some fixed and stochastic spatial sampling designs," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 56(2), pages 225-250, June.
    • Handle: RePEc:spr:aistmt:v:56:y:2004:i:2:p:225-250
    DOI: 10.1007/BF02530543
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02530543
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02530543?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. Bradley, Richard C., 1989. "A caution on mixing conditions for random fields," Statistics & Probability Letters, Elsevier, vol. 8(5), pages 489-491, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. S. N. Lahiri, 2018. "Uncertainty Quantification in Robust Inference for Irregularly Spaced Spatial Data Using Block Bootstrap," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 173-221, December.
    2. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Srijan Sengupta & Xiaofeng Shao & Yingchuan Wang, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 315-326, May.
    3. Bachoc, François, 2014. "Asymptotic analysis of the role of spatial sampling for covariance parameter estimation of Gaussian processes," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 1-35.

    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. Richard C. Bradley, 2001. "A Stationary Rho-Mixing Markov Chain Which Is Not “Interlaced” Rho-Mixing," Journal of Theoretical Probability, Springer, vol. 14(3), pages 717-727, July.
    2. Daniel Nordman, 2008. "An empirical likelihood method for spatial regression," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 68(3), pages 351-363, November.
    3. Burton, Robert M. & Steif, Jeffrey E., 1995. "Quite weak Bernoulli with exponential rate and percolation for random fields," Stochastic Processes and their Applications, Elsevier, vol. 58(1), pages 35-55, July.
    4. Nguyen, Hien D. & McLachlan, Geoffrey J., 2018. "Chunked-and-averaged estimators for vector parameters," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 336-342.
    5. Bradley, Richard C., 1997. "Every "lower psi-mixing" Markov chain is "interlaced rho-mixing"," Stochastic Processes and their Applications, Elsevier, vol. 72(2), pages 221-239, December.
    6. S. N. Lahiri, 2018. "Uncertainty Quantification in Robust Inference for Irregularly Spaced Spatial Data Using Block Bootstrap," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 173-221, December.
    7. Salim Bouzebda & Inass Soukarieh, 2022. "Non-Parametric Conditional U -Processes for Locally Stationary Functional Random Fields under Stochastic Sampling Design," Mathematics, MDPI, vol. 11(1), pages 1-69, December.
    8. Salim Bouzebda, 2024. "Limit Theorems in the Nonparametric Conditional Single-Index U -Processes for Locally Stationary Functional Random Fields under Stochastic Sampling Design," Mathematics, MDPI, vol. 12(13), pages 1-81, June.
    9. Volný, Dalibor & Wang, Yizao, 2014. "An invariance principle for stationary random fields under Hannan’s condition," Stochastic Processes and their Applications, Elsevier, vol. 124(12), pages 4012-4029.

    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:aistmt:v:56:y:2004:i:2:p:225-250. 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.