IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i24p3272-d704120.html
   My bibliography  Save this article

Generalized Confidence Intervals for Zero-Inflated Pareto Distribution

Author

Listed:
  • Xiao Wang

    (School of Mathematics and Statistics, Qingdao University, Qingdao 266000, China
    Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100049, China)

  • Xinmin Li

    (School of Mathematics and Statistics, Qingdao University, Qingdao 266000, China)

Abstract

This paper considers interval estimations for the mean of Pareto distribution with excess zeros. Three approaches for interval estimation are proposed based on fiducial generalized pivotal quantities (FGPQs), respectively. Simulation studies are performed to assess the performance of the proposed methods, along with three measurements to determine comparisons with competing approaches. The advantages and disadvantages of each method are provided. The methods are illustrated using a real phone call dataset.

Suggested Citation

  • Xiao Wang & Xinmin Li, 2021. "Generalized Confidence Intervals for Zero-Inflated Pareto Distribution," Mathematics, MDPI, vol. 9(24), pages 1-9, December.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:24:p:3272-:d:704120
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/24/3272/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/24/3272/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Badiollah Asrabadi, 1990. "Estimation in the pareto distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 37(1), pages 199-205, December.
    2. Wu, Shu-Fei, 2008. "Interval estimation for a Pareto distribution based on a doubly type II censored sample," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3779-3788, March.
    3. Zhenmin Chen, 1996. "Joint confidence region for the parameters of pareto distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 44(1), pages 191-197, December.
    Full references (including those not matched with items on IDEAS)

    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. Fen Jiang & Junmei Zhou & Jin Zhang, 2020. "Restricted minimum volume confidence region for Pareto distribution," Statistical Papers, Springer, vol. 61(5), pages 2015-2029, October.
    2. Jin Zhang, 2013. "Simplification of joint confidence regions for the parameters of the Pareto distribution," Computational Statistics, Springer, vol. 28(4), pages 1453-1462, August.
    3. Fernández, Arturo J., 2012. "Minimizing the area of a Pareto confidence region," European Journal of Operational Research, Elsevier, vol. 221(1), pages 205-212.
    4. Fernández, Arturo J., 2013. "Smallest Pareto confidence regions and applications," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 11-25.
    5. Yogesh Tripathi & Somesh Kumar & Constantinos Petropoulos, 2016. "Estimating the shape parameter of a Pareto distribution under restrictions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(1), pages 91-111, January.
    6. Amal S. Hassan & Salwa M. Assar & Kareem A. Ali & Heba F. Nagy, 2021. "Estimation of the density and cumulative distribution functions of the exponentiated Burr XII distribution," Statistics in Transition New Series, Polish Statistical Association, vol. 22(4), pages 171-189, December.
    7. Wenshu Qian & Wangxue Chen & Xiaofang He, 2021. "Parameter estimation for the Pareto distribution based on ranked set sampling," Statistical Papers, Springer, vol. 62(1), pages 395-417, February.
    8. Volterman, William & Balakrishnan, N. & Cramer, Erhard, 2012. "Exact nonparametric meta-analysis for multiple independent doubly Type-II censored samples," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1243-1255.
    9. Yogesh Mani Tripathi & Amulya Kumar Mahto & Sanku Dey, 2017. "Efficient Estimation of the PDF and the CDF of a Generalized Logistic Distribution," Annals of Data Science, Springer, vol. 4(1), pages 63-81, March.
    10. Hassan Amal S. & Assar Salwa M. & Ali Kareem A. & Nagy Heba F., 2021. "Estimation of the density and cumulative distribution functions of the exponentiated Burr XII distribution," Statistics in Transition New Series, Polish Statistical Association, vol. 22(4), pages 171-189, December.
    11. Hanieh Panahi, 2019. "Estimation for the parameters of the Burr Type XII distribution under doubly censored sample with application to microfluidics data," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(4), pages 510-518, August.
    12. Cramer, Erhard & Schmiedt, Anja Bettina, 2011. "Progressively Type-II censored competing risks data from Lomax distributions," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1285-1303, March.
    13. Mehdi Jabbari Nooghabi, 2016. "Estimation of the Lomax Distribution in the Presence of Outliers," Annals of Data Science, Springer, vol. 3(4), pages 385-399, December.
    14. Wu, Shu-Fei, 2008. "Interval estimation for a Pareto distribution based on a doubly type II censored sample," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3779-3788, March.
    15. Liang Wang & Huizhong Lin & Yuhlong Lio & Yogesh Mani Tripathi, 2022. "Interval Estimation of Generalized Inverted Exponential Distribution under Records Data: A Comparison Perspective," Mathematics, MDPI, vol. 10(7), pages 1-20, March.
    16. Sanku Dey & Tanmay Kayal & Yogesh Mani Tripathi, 2018. "Evaluation and Comparison of Estimators in the Gompertz Distribution," Annals of Data Science, Springer, vol. 5(2), pages 235-258, June.

    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:gam:jmathe:v:9:y:2021:i:24:p:3272-:d:704120. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.