IDEAS home Printed from https://ideas.repec.org/a/spr/aodasc/v3y2016i4d10.1007_s40745-016-0087-7.html
   My bibliography  Save this article

Estimation of the Lomax Distribution in the Presence of Outliers

Author

Listed:
  • Mehdi Jabbari Nooghabi

    (Ferdowsi University of Mashhad)

Abstract

In this paper, we find the moment, maximum likelihood, least squares and weighted least squares estimators of the parameters of Lomax distribution in the presence of outliers. Also, the mixture estimator of these four methods is derived. Further, we discuss about the efficiency of the estimators. Analysis of a simulated data set and an actual example from an insurance company has been presented for illustrative purposes.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:aodasc:v:3:y:2016:i:4:d:10.1007_s40745-016-0087-7
    DOI: 10.1007/s40745-016-0087-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40745-016-0087-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40745-016-0087-7?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. 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. M. Jabbari Nooghabi & E. Khaleghpanah Nooghabi, 2016. "On entropy of a Pareto distribution in the presence of outliers," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(17), pages 5234-5250, September.
    3. 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.
    4. S. Saksena & A. Johnson, 1984. "Best unbiased estimators for the parameters of a two-parameter Pareto distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 31(1), pages 77-83, December.
    5. H. Malik, 1970. "Estimation of the parameters of the Pareto distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 15(1), pages 126-132, December.
    6. Douglas M. Hawkins, 1980. "Critical Values for Identifying Outliers," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 95-96, March.
    7. Howlader, Hatem A. & Hossain, Anwar M., 2002. "Bayesian survival estimation of Pareto distribution of the second kind based on failure-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 38(3), pages 301-314, January.
    8. M. Ahsanullah, 1991. "Record values of the Lomax distribution," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 45(1), pages 21-29, March.
    9. Aaron Childs & N. Balakrishnan & Mohamed Moshref, 2001. "Order statistics from non-identical right-truncated Lomax random variables with applications," Statistical Papers, Springer, vol. 42(2), pages 187-206, April.
    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. Amal S. Hassan & E. A. Elsherpieny & Rokaya E. Mohamed, 2023. "Classical and Bayesian Estimation of Entropy for Pareto Distribution in Presence of Outliers with Application," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 707-740, February.

    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. Hurairah Ahmed & Alabid Abdelhakim, 2020. "Beta transmuted Lomax distribution with applications," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 13-34, June.
    2. Ahmed Hurairah & Abdelhakim Alabid, 2020. "Beta transmuted Lomax distribution with applications," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 13-34, June.
    3. 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.
    4. Elfessi, Abdulaziz & Chun Jin, 1996. "On robust estimation of the common scale parameter of several Pareto distributions," Statistics & Probability Letters, Elsevier, vol. 29(4), pages 345-352, September.
    5. 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.
    6. Amal S. Hassan & E. A. Elsherpieny & Rokaya E. Mohamed, 2023. "Classical and Bayesian Estimation of Entropy for Pareto Distribution in Presence of Outliers with Application," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 707-740, February.
    7. Vijay K. Rohatgi & A. K. Md. Ehsanes Saleh, 1987. "Estimation of the common scale parameter of two pareto distributions in censored samples," Naval Research Logistics (NRL), John Wiley & Sons, vol. 34(2), pages 235-238, April.
    8. Manoj Chacko & Rakhi Mohan, 2019. "Bayesian analysis of Weibull distribution based on progressive type-II censored competing risks data with binomial removals," Computational Statistics, Springer, vol. 34(1), pages 233-252, March.
    9. 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.
    10. Rui Hua & Wenhao Gui, 2022. "Revisit to progressively Type-II censored competing risks data from Lomax distributions," Journal of Risk and Reliability, , vol. 236(3), pages 377-394, June.
    11. Mehdi Jabbari Nooghabi, 2021. "Comparing estimation of the parameters of distribution of the root density of plants in the presence of outliers," Environmetrics, John Wiley & Sons, Ltd., vol. 32(5), August.
    12. Amal S. Hassan & Ibrahim M. Almanjahie & Amer Ibrahim Al-Omari & Loai Alzoubi & Heba Fathy Nagy, 2023. "Stress–Strength Modeling Using Median-Ranked Set Sampling: Estimation, Simulation, and Application," Mathematics, MDPI, vol. 11(2), pages 1-19, January.
    13. Aaron Childs, 2003. "Higher order moments of order statistics from INID exponential random variables," Statistical Papers, Springer, vol. 44(2), pages 151-167, April.
    14. Damian Przekop, 2020. "Feature Engineering for Anti-Fraud Models Based on Anomaly Detection," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(3), pages 301-316, September.
    15. Francesca Ieva & Anna Maria Paganoni, 2020. "Component-wise outlier detection methods for robustifying multivariate functional samples," Statistical Papers, Springer, vol. 61(2), pages 595-614, April.
    16. BuHamra, Sana S. & Al-Kandari, N.M.Noriah M. & Ahmed, S. E., 2004. "Inference concerning quantile for left truncated and right censored data," Computational Statistics & Data Analysis, Elsevier, vol. 46(4), pages 819-831, July.
    17. Okhli, Kheirolah & Jabbari Nooghabi, Mehdi, 2023. "On the three-component mixture of exponential distributions: A Bayesian framework to model data with multiple lower and upper outliers," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 208(C), pages 480-500.
    18. Gaucher, Solenne & Klopp, Olga & Robin, Geneviève, 2021. "Outlier detection in networks with missing links," Computational Statistics & Data Analysis, Elsevier, vol. 164(C).
    19. Andrzej Chmielowiec, 2021. "Algorithm for error-free determination of the variance of all contiguous subsequences and fixed-length contiguous subsequences for a sequence of industrial measurement data," Computational Statistics, Springer, vol. 36(4), pages 2813-2840, December.
    20. Marc Chataigner & Stéphane Crépey & Jiang Pu, 2020. "Nowcasting Networks," Post-Print hal-03910123, HAL.

    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:aodasc:v:3:y:2016:i:4:d:10.1007_s40745-016-0087-7. 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.