IDEAS home Printed from https://ideas.repec.org/a/spr/aodasc/v8y2021i3d10.1007_s40745-020-00243-7.html
   My bibliography  Save this article

On Discrimination Between the Lindley and xgamma Distributions

Author

Listed:
  • Subhradev Sen

    (Alliance University)

  • Hazem Al-Mofleh

    (Tafila Technical University)

  • Sudhansu S. Maiti

    (Visva Bharati University)

Abstract

For a given data set the problem of selecting either Lindley or xgamma distribution with unknown parameter is investigated in this article. Both these distributions can be used quite effectively for analyzing skewed non-negative data and in modeling time-to-event data sets. We have used the ratio of the maximized likelihoods in choosing between the Lindley and xgamma distributions. Asymptotic distributions of the ratio of the maximized likelihoods are obtained and those are utilized to determine the minimum sample size required to discriminate between these two distributions for user specified probability of correct selection and tolerance limit.

Suggested Citation

  • Subhradev Sen & Hazem Al-Mofleh & Sudhansu S. Maiti, 2021. "On Discrimination Between the Lindley and xgamma Distributions," Annals of Data Science, Springer, vol. 8(3), pages 559-575, September.
    • Handle: RePEc:spr:aodasc:v:8:y:2021:i:3:d:10.1007_s40745-020-00243-7
    DOI: 10.1007/s40745-020-00243-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40745-020-00243-7
    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/s40745-020-00243-7?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. Rasool Roozegar & Saralees Nadarajah, 2017. "On a Generalized Lindley Distribution," Statistica, Department of Statistics, University of Bologna, vol. 77(2), pages 149-157.
    2. M. E. Ghitany & D. K. Al-Mutairi, 2008. "Size-biased Poisson-Lindley distribution and its application," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 299-311.
    3. Ghitany, M.E. & Al-Mutairi, D.K. & Balakrishnan, N. & Al-Enezi, L.J., 2013. "Power Lindley distribution and associated inference," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 20-33.
    4. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    5. D. S. Shibu & M. R. Irshad, 2016. "Extended New Generalized Lindley Distribution," Statistica, Department of Statistics, University of Bologna, vol. 76(1), pages 41-56.
    6. A. Asgharzadeh & S. Nadarajah & F. Sharafi, 2017. "Generalized inverse Lindley distribution with application to Danish fire insurance data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(10), pages 5001-5021, May.
    7. Ghitany, M.E. & Al-Mutairi, D.K. & Nadarajah, S., 2008. "Zero-truncated Poisson–Lindley distribution and its application," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 279-287.
    8. Ghitany, M.E. & Atieh, B. & Nadarajah, S., 2008. "Lindley distribution and its application," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(4), pages 493-506.
    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. Mario A. Rojas & Yuri A. Iriarte, 2022. "A Lindley-Type Distribution for Modeling High-Kurtosis Data," Mathematics, MDPI, vol. 10(13), pages 1-19, June.
    2. Amal S. Hassan & Said G. Nassr, 2019. "Power Lindley-G Family of Distributions," Annals of Data Science, Springer, vol. 6(2), pages 189-210, June.
    3. Devendra Kumar & Anju Goyal, 2019. "Generalized Lindley Distribution Based on Order Statistics and Associated Inference with Application," Annals of Data Science, Springer, vol. 6(4), pages 707-736, December.
    4. Jiaxin Nie & Wenhao Gui, 2019. "Parameter Estimation of Lindley Distribution Based on Progressive Type-II Censored Competing Risks Data with Binomial Removals," Mathematics, MDPI, vol. 7(7), pages 1-15, July.
    5. Festus C. Opone & Nosakhare Ekhosuehi & Sunday E. Omosigho, 2022. "Topp-Leone Power Lindley Distribution(Tlpld): its Properties and Application," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 597-608, August.
    6. Cesar Augusto Taconeli & Suely Ruiz Giolo, 2020. "Maximum likelihood estimation based on ranked set sampling designs for two extensions of the Lindley distribution with uncensored and right-censored data," Computational Statistics, Springer, vol. 35(4), pages 1827-1851, December.
    7. Ahmed M. T. Abd El-Bar & Willams B. F. da Silva & Abraão D. C. Nascimento, 2021. "An Extended log-Lindley-G Family: Properties and Experiments in Repairable Data," Mathematics, MDPI, vol. 9(23), pages 1-15, December.
    8. Iman Makhdoom & Parviz Nasiri & Abbas Pak, 2016. "Bayesian approach for the reliability parameter of power Lindley distribution," 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. 7(3), pages 341-355, September.
    9. Shikhar Tyagi & Arvind Pandey & Christophe Chesneau, 2022. "Weighted Lindley Shared Regression Model for Bivariate Left Censored Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 655-682, November.
    10. Mahendra Saha & Harsh Tripathi & Sanku Dey & Sudhansu S. Maiti, 2021. "Acceptance sampling inspection plan for the Lindley and power Lindley distributed quality characteristics," 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. 12(6), pages 1410-1419, December.
    11. A. Shabani & M. Khaleghi Moghadam & A. Gholami & E. Moradi, 2018. "Exponentiated Power Lindley Logarithmic: Model, Properties and Applications," Annals of Data Science, Springer, vol. 5(4), pages 583-613, December.
    12. Rama Shanker, 2016. "Sujatha Distribution And Its Applications," Statistics in Transition New Series, Polish Statistical Association, vol. 17(3), pages 391-410, September.
    13. Shukla Kamlesh Kumar & Shanker Rama, 2018. "Power Ishita Distribution And Its Application To Model Lifetime Data," Statistics in Transition New Series, Statistics Poland, vol. 19(1), pages 135-148, March.
    14. Wenhao Gui & Huainian Zhang & Lei Guo, 2017. "The Complementary Lindley-Geometric Distribution and Its Application in Lifetime Analysis," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 79(2), pages 316-335, November.
    15. V. Ranjbar & M. Alizadeh & G. G. Hademani, 2018. "Extended Exponentiated Power Lindley Distribution," Statistics in Transition New Series, Polish Statistical Association, vol. 19(4), pages 621-643, December.
    16. Sanku Dey & Indranil Ghosh & Devendra Kumar, 2019. "Alpha-Power Transformed Lindley Distribution: Properties and Associated Inference with Application to Earthquake Data," Annals of Data Science, Springer, vol. 6(4), pages 623-650, December.
    17. Muhammad Aslam Mohd Safari & Nurulkamal Masseran & Muhammad Hilmi Abdul Majid, 2020. "Robust Reliability Estimation for Lindley Distribution—A Probability Integral Transform Statistical Approach," Mathematics, MDPI, vol. 8(9), pages 1-21, September.
    18. Morad Alizadeh & Emrah Altun & Gamze Ozel & Mahmoud Afshari & Abbas Eftekharian, 2019. "A New Odd Log-Logistic Lindley Distribution with Properties and Applications," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 323-346, December.
    19. Kamlesh Kumar Shukla & Rama Shanker, 2018. "Power Ishita Distribution And Its Application To Model Lifetime Data," Statistics in Transition New Series, Polish Statistical Association, vol. 19(1), pages 135-148, March.
    20. Shanker R & Kamlesh KK & Fesshaye H, 2017. "A Two Parameter Lindley Distribution: Its Properties and Applications," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 1(4), pages 85-90, May.

    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:8:y:2021:i:3:d:10.1007_s40745-020-00243-7. 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.