IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v61y2013icp99-106.html
   My bibliography  Save this article

Conditional tests for homogeneity of zero-inflated Poisson and Poisson-hurdle distributions

Author

Listed:
  • Bedrick, Edward J.
  • Hossain, Anwar

Abstract

We develop two conditional tests for homogeneity of zero-inflated Poisson (ZIP) and Poisson-hurdle distributions. A Monte Carlo method is proposed for approximating the reference distributions of these tests. The techniques are applied to two examples.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:csdana:v:61:y:2013:i:c:p:99-106
    DOI: 10.1016/j.csda.2012.11.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947312004008
    Download Restriction: Full text for ScienceDirect subscribers only.
    File URL: https://libkey.io/10.1016/j.csda.2012.11.009?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. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    2. Karen E. Han & Paul J. Catalano & Pralay Senchaudhuri & Cyrus Mehta, 2004. "Exact Analysis of Dose Response for Multiple Correlated Binary Outcomes," Biometrics, The International Biometric Society, vol. 60(1), pages 216-224, March.
    3. 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.
    4. Chris Corcoran & Louise Ryan & Pralay Senchaudhuri & Cyrus Mehta & Nitin Patel & Geert Molenberghs, 2001. "An Exact Trend Test for Correlated Binary Data," Biometrics, The International Biometric Society, vol. 57(3), pages 941-948, September.
    5. 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.
    6. Martin Ridout & John Hinde & Clarice G. B. Demétrio, 2001. "A Score Test for Testing a Zero‐Inflated Poisson Regression Model Against Zero‐Inflated Negative Binomial Alternatives," Biometrics, The International Biometric Society, vol. 57(1), pages 219-223, March.
    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. Wang, Chunlin & Marriott, Paul & Li, Pengfei, 2017. "Testing homogeneity for multiple nonnegative distributions with excess zero observations," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 146-157.
    2. Liu, Yin & Tian, Guo-Liang, 2015. "Type I multivariate zero-inflated Poisson distribution with applications," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 200-222.

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Derek S. Young & Andrew M. Raim & Nancy R. Johnson, 2017. "Zero-inflated modelling for characterizing coverage errors of extracts from the US Census Bureau's Master Address File," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 73-97, January.
    10. Zhen Xu & G. Cornelis van Kooten, 2013. "Count Models and Wildfire in British Columbia," Working Papers 2013-06, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    11. Tianji Cai & Yiwei Xia & Yisu Zhou, 2021. "Generalized Inflated Discrete Models: A Strategy to Work with Multimodal Discrete Distributions," Sociological Methods & Research, , vol. 50(1), pages 365-400, February.
    12. Cai, Tianji & Xia, Yiwei & Zhou, Yisu, 2017. "Generalized Inflated Discrete Models: A Strategy to Work with Multimodal Discrete Distributions," SocArXiv 4r2j3, Center for Open Science.
    13. Garay, Aldo M. & Hashimoto, Elizabeth M. & Ortega, Edwin M.M. & Lachos, Víctor H., 2011. "On estimation and influence diagnostics for zero-inflated negative binomial regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1304-1318, March.
    14. Habtamu K. Benecha & Brian Neelon & Kimon Divaris & John S. Preisser, 2017. "Marginalized mixture models for count data from multiple source populations," Journal of Statistical Distributions and Applications, Springer, vol. 4(1), pages 1-17, December.
    15. Hadi Saboori & Mahdi Doostparast, 2024. "Control Charts Based on Zero to k Inflated Power Series Regression Models and Their Applications," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 86(2), pages 442-476, November.
    16. Abbas Moghimbeigi & Mohammed Reza Eshraghian & Kazem Mohammad & Brian Mcardle, 2008. "Multilevel zero-inflated negative binomial regression modeling for over-dispersed count data with extra zeros," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(10), pages 1193-1202.
    17. T. Martin Lukusa & Shen-Ming Lee & Chin-Shang Li, 2016. "Semiparametric estimation of a zero-inflated Poisson regression model with missing covariates," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(4), pages 457-483, May.
    18. Maria del Carmen Melgar & Jose Antonio Ordaz, 2010. "The Utility Of Zero-Inflated Models In The Estimation Of The Number Of Accidents In The Automobile Insurance Industry," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 5(2), pages 181-194, December.
    19. 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.
    20. Cindy Xin Feng, 2021. "A comparison of zero-inflated and hurdle models for modeling zero-inflated count data," Journal of Statistical Distributions and Applications, Springer, vol. 8(1), pages 1-19, December.

    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:61:y:2013:i:c:p:99-106. 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.