IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v29y2008i2p402-420.html
   My bibliography  Save this article

GQL Versus Conditional GQL Inferences for Non‐Stationary Time Series of Counts with Overdispersion

Author

Listed:
  • Taslim S. Mallick
  • Brajendra C. Sutradhar

Abstract

. This article proposes an autoregressive model for time series of counts with non‐stationary means, variances and covariances as functions of certain time‐dependant covariates. For the estimation of the regression, overdispersion and correlation index parameters, a conditional generalized quasilikelihood (CGQL) approach is developed under the assumption that the count responses marginally satisfy the first two moments of a negative binomial distribution. Thus this CGQL approach avoids the use of the likelihood or so‐called partial likelihood of the data which are known to be extremely complicated in the present non‐stationary time series set‐up. It is shown through an extensive simulation study that the proposed CGQL approach performs very well in estimating the parameters of the model. This is also shown that the CGQL approach performs better than an existing GQL approach, especially for the estimation of the overdispersion parameter of the model.

Suggested Citation

  • Taslim S. Mallick & Brajendra C. Sutradhar, 2008. "GQL Versus Conditional GQL Inferences for Non‐Stationary Time Series of Counts with Overdispersion," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(2), pages 402-420, March.
    • Handle: RePEc:bla:jtsera:v:29:y:2008:i:2:p:402-420
    DOI: 10.1111/j.1467-9892.2007.00570.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9892.2007.00570.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9892.2007.00570.x?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
    ---><---

    Citations

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


    Cited by:

    1. R. Prabhakar Rao & Brajendra C. Sutradhar, 2020. "Multiple Categorical Covariates-Based Multinomial Dynamic Response Model," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(1), pages 186-219, February.
    2. Brajendra C. Sutradhar & Vandna Jowaheer & R. Prabhakar Rao, 2016. "Semi-Parametric Models for Negative Binomial Panel Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 78(2), pages 269-303, August.
    3. Yuvraj Sunecher & Naushad Mamode Khan & Miroslav M. Ristić & Vandna Jowaheer, 2019. "BINAR(1) negative binomial model for bivariate non-stationary time series with different over-dispersion indices," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 625-653, December.
    4. Pushpakanthie Wijekoon & Alwell Oyet & Brajendra C. Sutradhar, 2019. "Pair-Wise Family-Based Correlation Model for Spatial Count Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 133-184, June.
    5. Brajendra C. Sutradhar & R. Prabhakar Rao, 2016. "Inferences in Longitudinal Count Data Models with Measurement Errors in Time Dependent Covariates," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 78(1), pages 39-65, May.

    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:bla:jtsera:v:29:y:2008:i:2:p:402-420. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.