IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v38y2001i2p191-201.html
   My bibliography  Save this article

Zero-inflated Poisson model in statistical process control

Author

Listed:
  • Xie, M.
  • He, B.
  • Goh, T. N.

Abstract

No abstract is available for this item.

Suggested Citation

  • Xie, M. & He, B. & Goh, T. N., 2001. "Zero-inflated Poisson model in statistical process control," Computational Statistics & Data Analysis, Elsevier, vol. 38(2), pages 191-201, December.
  • Handle: RePEc:eee:csdana:v:38:y:2001:i:2:p:191-201
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(01)00033-0
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    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. Freund, Deborah A. & Kniesner, Thomas J. & LoSasso, Anthony T., 1999. "Dealing with the common econometric problems of count data with excess zeros, endogenous treatment effects, and attrition bias," Economics Letters, Elsevier, vol. 62(1), pages 7-12, January.
    2. D. Böhning & E. Dietz & P. Schlattmann & L. Mendonça & U. Kirchner, 1999. "The zero‐inflated Poisson model and the decayed, missing and filled teeth index in dental epidemiology," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(2), pages 195-209.
    3. Gupta, Pushpa L. & Gupta, Ramesh C. & Tripathi, Ram C., 1996. "Analysis of zero-adjusted count data," Computational Statistics & Data Analysis, Elsevier, vol. 23(2), pages 207-218, December.
    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. Xu, Hai-Yan & Xie, Min & Goh, Thong Ngee & Fu, Xiuju, 2012. "A model for integer-valued time series with conditional overdispersion," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4229-4242.
    2. Helai Huang & Hong Chin, 2010. "Modeling road traffic crashes with zero-inflation and site-specific random effects," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(3), pages 445-462, August.
    3. Olivier Thas & J. C. W. Rayner, 2005. "Smooth Tests for the Zero-Inflated Poisson Distribution," Biometrics, The International Biometric Society, vol. 61(3), pages 808-815, September.
    4. Baksh, M. Fazil & Böhning, Dankmar & Lerdsuwansri, Rattana, 2011. "An extension of an over-dispersion test for count data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 466-474, January.
    5. Jun Yang & Min Xie & Thong Ngee Goh, 2011. "Outlier identification and robust parameter estimation in a zero-inflated Poisson model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(2), pages 421-430, October.
    6. Höhle, Michael & Paul, Michaela, 2008. "Count data regression charts for the monitoring of surveillance time series," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4357-4368, May.
    7. Chang, Fengming M. & Chen, Long-Hui & Chen, Yueh-Li & Huang, Chien-Yu, 2008. "Approximate distribution of demerit statistic--A bounding approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3300-3309, March.
    8. Baíllo, A. & Berrendero, J.R. & Cárcamo, J., 2009. "Tests for zero-inflation and overdispersion: A new approach based on the stochastic convex order," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2628-2639, May.
    9. E. Bahrami Samani & Y. Amirian & M. Ganjali, 2012. "Likelihood estimation for longitudinal zero-inflated power series regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 1965-1974, May.

    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. Yip, Karen C.H. & Yau, Kelvin K.W., 2005. "On modeling claim frequency data in general insurance with extra zeros," Insurance: Mathematics and Economics, Elsevier, vol. 36(2), pages 153-163, April.
    2. Baíllo, A. & Berrendero, J.R. & Cárcamo, J., 2009. "Tests for zero-inflation and overdispersion: A new approach based on the stochastic convex order," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2628-2639, May.
    3. Bae, S. & Famoye, F. & Wulu, J.T. & Bartolucci, A.A. & Singh, K.P., 2005. "A rich family of generalized Poisson regression models with applications," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 69(1), pages 4-11.
    4. E. Bahrami Samani & Y. Amirian & M. Ganjali, 2012. "Likelihood estimation for longitudinal zero-inflated power series regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 1965-1974, May.
    5. Bedrick, Edward J. & Hossain, Anwar, 2013. "Conditional tests for homogeneity of zero-inflated Poisson and Poisson-hurdle distributions," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 99-106.
    6. Yanlin Tang & Liya Xiang & Zhongyi Zhu, 2014. "Risk Factor Selection in Rate Making: EM Adaptive LASSO for Zero‐Inflated Poisson Regression Models," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1112-1127, June.
    7. Grün, Bettina & Leisch, Friedrich, 2008. "FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i04).
    8. Sarah Brown & Alan Duncan & Mark N. Harris & Jennifer Roberts & Karl Taylor, 2015. "A Zero-Inflated Regression Model for Grouped Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(6), pages 822-831, December.
    9. Aldo M. Garay & Victor H. Lachos & Heleno Bolfarine, 2015. "Bayesian estimation and case influence diagnostics for the zero-inflated negative binomial regression model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(6), pages 1148-1165, June.
    10. Hossein Kavand & Marcel Voia, 2018. "Estimation of Health Care Demand and its Implication on Income Effects of Individuals," Springer Proceedings in Business and Economics, in: William H. Greene & Lynda Khalaf & Paul Makdissi & Robin C. Sickles & Michael Veall & Marcel-Cristia (ed.), Productivity and Inequality, pages 275-304, Springer.
    11. Tousifur Rahman & Partha Jyoti Hazarika & M. Masoom Ali & Manash Pratim Barman, 2022. "Three-Inflated Poisson Distribution and its Application in Suicide Cases of India During Covid-19 Pandemic," Annals of Data Science, Springer, vol. 9(5), pages 1103-1127, October.
    12. Feng-Chang Xie & Jin-Guan Lin & Bo-Cheng Wei, 2014. "Bayesian zero-inflated generalized Poisson regression model: estimation and case influence diagnostics," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(6), pages 1383-1392, June.
    13. Jussiane Nader Gonçalves & Wagner Barreto-Souza, 2020. "Flexible regression models for counts with high-inflation of zeros," METRON, Springer;Sapienza Università di Roma, vol. 78(1), pages 71-95, April.
    14. Sunisa Junnumtuam & Sa-Aat Niwitpong & Suparat Niwitpong, 2022. "A Zero-and-One Inflated Cosine Geometric Distribution and Its Application," Mathematics, MDPI, vol. 10(21), pages 1-22, October.
    15. Feng, Jiarui & Zhu, Zhongyi, 2011. "Semiparametric analysis of longitudinal zero-inflated count data," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 61-72, January.
    16. Bermúdez, Lluís & Karlis, Dimitris, 2011. "Bayesian multivariate Poisson models for insurance ratemaking," Insurance: Mathematics and Economics, Elsevier, vol. 48(2), pages 226-236, March.
    17. L. Elbakidze & Y. H. Jin, 2015. "Are Economic Development and Education Improvement Associated with Participation in Transnational Terrorism?," Risk Analysis, John Wiley & Sons, vol. 35(8), pages 1520-1535, August.
    18. Gian Luigi Albano & Federico Dini & Roberto Zampino & Marta Fana, 2008. "The Determinants of Suppliers’ Performance in E-Procurement: Evidence from the Italian Government’s E-Procurement Platform," Working Papers 2008.49, Fondazione Eni Enrico Mattei.
    19. K. F. Lam & Hongqi Xue & Yin Bun Cheung, 2006. "Semiparametric Analysis of Zero-Inflated Count Data," Biometrics, The International Biometric Society, vol. 62(4), pages 996-1003, December.
    20. Markus Jochmann, 2013. "What belongs where? Variable selection for zero-inflated count models with an application to the demand for health care," Computational Statistics, Springer, vol. 28(5), pages 1947-1964, October.

    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:eee:csdana:v:38:y:2001:i:2:p:191-201. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.