IDEAS home Printed from https://ideas.repec.org/a/spr/aistmt/v62y2010i1p91-107.html
   My bibliography  Save this article

Finding market structure by sales count dynamics—Multivariate structural time series models with hierarchical structure for count data—

Author

Listed:
  • Nobuhiko Terui
  • Masataka Ban
  • Toshihiko Maki

Abstract

No abstract is available for this item.

Suggested Citation

  • Nobuhiko Terui & Masataka Ban & Toshihiko Maki, 2010. "Finding market structure by sales count dynamics—Multivariate structural time series models with hierarchical structure for count data—," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(1), pages 91-107, February.
    • Handle: RePEc:spr:aistmt:v:62:y:2010:i:1:p:91-107
    DOI: 10.1007/s10463-009-0244-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10463-009-0244-2
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10463-009-0244-2?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. Harvey, Andrew C & Fernandes, C, 1989. "Time Series Models for Count or Qualitative Observations," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 407-417, October.
    2. Harvey, Andrew C & Fernandes, C, 1989. "Time Series Models for Count or Qualitative Observations: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 422-422, October.
    3. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    4. Rajiv Grover & William R. Dillon, 1985. "A Probabilistic Model For Testing Hypothesized Hierarchical Market Structures," Marketing Science, INFORMS, vol. 4(4), pages 312-335.
    5. Glen L. Urban & Philip L. Johnson & John R. Hauser, 1984. "Testing Competitive Market Structures," Marketing Science, INFORMS, vol. 3(2), pages 83-112.
    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. Nobuhiko Terui & Shohei Hasegawa, 2013. "Modeling Preference Change through Brand Satiation," TMARG Discussion Papers 112, Graduate School of Economics and Management, Tohoku University.
    2. Nobuhiko Terui & Shohei Hasegawa & Greg M. Allenby, 2015. "A Threshold Model for Discontinuous Preference Change and Satiation," TMARG Discussion Papers 122, Graduate School of Economics and Management, Tohoku University.
    3. Nobuhiko Terui & Masataka Ban, 2013. "Multivariate Time Series Model with Hierarchical Structure for Over-dispersed Discrete Outcomes," TMARG Discussion Papers 113, Graduate School of Economics and Management, Tohoku University, revised Aug 2013.

    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. Nobuhiko Terui & Masataka Ban, 2013. "Multivariate Time Series Model with Hierarchical Structure for Over-dispersed Discrete Outcomes," TMARG Discussion Papers 113, Graduate School of Economics and Management, Tohoku University, revised Aug 2013.
    2. Dani Gamerman & Thiago Rezende Santos & Glaura C. Franco, 2013. "A Non-Gaussian Family Of State-Space Models With Exact Marginal Likelihood," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(6), pages 625-645, November.
    3. Harvey, A., 2008. "Dynamic distributions and changing copulas," Cambridge Working Papers in Economics 0839, Faculty of Economics, University of Cambridge.
    4. Yang Lu, 2020. "A simple parameter‐driven binary time series model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 187-199, March.
    5. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    6. 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.
    7. Wagner Barreto-Souza, 2019. "Mixed Poisson INAR(1) processes," Statistical Papers, Springer, vol. 60(6), pages 2119-2139, December.
    8. Brannas, Kurt, 1995. "Prediction and control for a time-series count data model," International Journal of Forecasting, Elsevier, vol. 11(2), pages 263-270, June.
    9. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    10. Youn Ahn, Jae & Jeong, Himchan & Lu, Yang, 2021. "On the ordering of credibility factors," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 626-638.
    11. HEINEN, Andréas, 2003. "Modelling time series count data: an autoregressive conditional Poisson model," LIDAM Discussion Papers CORE 2003062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Han, Yang & Liu, Zehao & Ma, Jun, 2020. "Growth cycles and business cycles of the Chinese economy through the lens of the unobserved components model," China Economic Review, Elsevier, vol. 63(C).
    13. Yang Lu, 2018. "Dynamic Frailty Count Process in Insurance: A Unified Framework for Estimation, Pricing, and Forecasting," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 85(4), pages 1083-1102, December.
    14. Harvey, Andrew, 2010. "Tracking a changing copula," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 485-500, June.
    15. Ord, J. Keith & Koehler, Anne B. & Snyder, Ralph D. & Hyndman, Rob J., 2009. "Monitoring processes with changing variances," International Journal of Forecasting, Elsevier, vol. 25(3), pages 518-525, July.
    16. Shang, Zuofeng, 2012. "On latent process models in multi-dimensional space," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1259-1266.
    17. Robert Jung & A. Tremayne, 2011. "Useful models for time series of counts or simply wrong ones?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 59-91, March.
    18. Shirozhan, M. & Bakouch, Hassan S. & Mohammadpour, M., 2023. "A flexible INAR(1) time series model with dependent zero-inflated count series and medical contagious cases," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 206(C), pages 216-230.
    19. Kuk, Anthony Y. C., 1999. "The use of approximating models in Monte Carlo maximum likelihood estimation," Statistics & Probability Letters, Elsevier, vol. 45(4), pages 325-333, December.
    20. Ki Hong Kim & Young Jae Han & Sugil Lee & Sung Won Cho & Chulung Lee, 2019. "Text Mining for Patent Analysis to Forecast Emerging Technologies in Wireless Power Transfer," Sustainability, MDPI, vol. 11(22), pages 1-24, November.

    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:62:y:2010:i:1:p:91-107. 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.