IDEAS home Printed from https://ideas.repec.org/a/bpj/strimo/v30y2013i3p221-235n3.html
   My bibliography  Save this article

Conditional L1 estimation for random coefficient integer-valued autoregressive processes

Author

Listed:
  • Chen Xi
  • Wang Lihong

    () (Department of Mathematics, Nanjing University, Nanjing, P.R. China)

Abstract

In this paper we study the integer-valued autoregressive model, which belongs to the class of thinning models with count data.We mainly focus on the random coefficient integer-valued autoregressive (RCINAR) model and propose a conditional least absolute deviation (CL1) method to estimate the parameters of the model. The asymptotic distribution of the CL1 estimator is investigated. The finite sample performance of the proposed estimator is evaluated through simulation, and is compared with that of conditional least squares (CL2) estimation method. Simulation results show that the proposed method is effective and robust against outliers

Suggested Citation

  • Chen Xi & Wang Lihong, 2013. "Conditional L1 estimation for random coefficient integer-valued autoregressive processes," Statistics & Risk Modeling, De Gruyter, vol. 30(3), pages 221-235, August.
  • Handle: RePEc:bpj:strimo:v:30:y:2013:i:3:p:221-235:n:3
    as

    Download full text from publisher

    File URL: https://www.degruyter.com/view/j/strm.2013.30.issue-3/strm.2013.1093/strm.2013.1093.xml?format=INT
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    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. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    2. Fukasawa, T. & Basawa, I. V., 2002. "Estimation for a class of generalized state-space time series models," Statistics & Probability Letters, Elsevier, vol. 60(4), pages 459-473, December.
    3. Wang, J. D., 1995. "Asymptotic Normality of L1-Estimators in Nonlinear Regression," Journal of Multivariate Analysis, Elsevier, vol. 54(2), pages 227-238, August.
    4. Silva, Isabel & Silva, M. Eduarda, 2006. "Asymptotic distribution of the Yule-Walker estimator for INAR(p) processes," Statistics & Probability Letters, Elsevier, vol. 76(15), pages 1655-1663, September.
    5. Davis, Richard A. & Knight, Keith & Liu, Jian, 1992. "M-estimation for autoregressions with infinite variance," Stochastic Processes and their Applications, Elsevier, vol. 40(1), pages 145-180, February.
    6. Richard A. Davis, 2003. "Observation-driven models for Poisson counts," Biometrika, Biometrika Trust, vol. 90(4), pages 777-790, December.
    7. Konstantinos Fokianos & Roland Fried, 2010. "Interventions in INGARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(3), pages 210-225, May.
    8. Jung, Robert C. & Tremayne, A.R., 2006. "Coherent forecasting in integer time series models," International Journal of Forecasting, Elsevier, vol. 22(2), pages 223-238.
    9. Haitao Zheng & Ishwar V. Basawa & Somnath Datta, 2006. "Inference for pth-order random coefficient integer-valued autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(3), pages 411-440, May.
    10. Robert Jung & Gerd Ronning & A. Tremayne, 2005. "Estimation in conditional first order autoregression with discrete support," Statistical Papers, Springer, vol. 46(2), pages 195-224, April.
    Full references (including those not matched with items on IDEAS)

    More about this item

    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:bpj:strimo:v:30:y:2013:i:3:p:221-235:n:3. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Peter Golla). General contact details of provider: https://www.degruyter.com .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.