IDEAS home Printed from https://ideas.repec.org/a/spr/metrik/v83y2020i4d10.1007_s00184-019-00743-4.html
   My bibliography  Save this article

A note on multiple roots of a likelihood equation for Weibull sequential order statistics

Author

Listed:
  • Marcus Johnen

    (RWTH Aachen University)

  • Stefan Bedbur

    (RWTH Aachen University)

  • Udo Kamps

    (RWTH Aachen University)

Abstract

A multi-sample set-up of sequential order statistics from Weibull distribution functions with known scale parameters and a common unknown shape parameter is considered. The respective likelihood equation may have multiple roots even in the single-sample case, which is demonstrated by a simple example and illustrated with a simulation study. Uniqueness of the root of the likelihood equation and of the maximum likelihood estimator is examined with respect to different models of ordered data, sufficient conditions for uniqueness are shown, and the distribution of the number of roots of the likelihood equation is seen to be independent of the unknown shape parameter.

Suggested Citation

  • Marcus Johnen & Stefan Bedbur & Udo Kamps, 2020. "A note on multiple roots of a likelihood equation for Weibull sequential order statistics," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(4), pages 519-525, May.
    • Handle: RePEc:spr:metrik:v:83:y:2020:i:4:d:10.1007_s00184-019-00743-4
    DOI: 10.1007/s00184-019-00743-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00184-019-00743-4
    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/s00184-019-00743-4?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, Q.N. & Bedbur, S. & Kamps, U., 2013. "Distances between models of generalized order statistics," Journal of Multivariate Analysis, Elsevier, vol. 118(C), pages 24-36.
    2. Balakrishnan, N. & Kateri, M., 2008. "On the maximum likelihood estimation of parameters of Weibull distribution based on complete and censored data," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2971-2975, December.
    3. Erhard Cramer & Udo Kamps, 1996. "Sequential order statistics and k-out-of-n systems with sequentially adjusted failure rates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 48(3), pages 535-549, September.
    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. Bedbur, Stefan & Johnen, Marcus & Kamps, Udo, 2019. "Inference from multiple samples of Weibull sequential order statistics," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 381-399.
    2. Alexander Katzur & Udo Kamps, 2020. "Classification using sequential order statistics," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(1), pages 201-230, March.
    3. Pareek, Bhuvanesh & Kundu, Debasis & Kumar, Sumit, 2009. "On progressively censored competing risks data for Weibull distributions," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4083-4094, October.
    4. Coria, V.H. & Maximov, S. & Rivas-Dávalos, F. & Melchor, C.L. & Guardado, J.L., 2015. "Analytical method for optimization of maintenance policy based on available system failure data," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 55-63.
    5. Benjamin Laumen & Erhard Cramer, 2021. "k‐step stage life testing," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(2), pages 203-233, May.
    6. Tzong-Ru Tsai & Yuhlong Lio & Jyun-You Chiang & Yi-Jia Huang, 2022. "A New Process Performance Index for the Weibull Distribution with a Type-I Hybrid Censoring Scheme," Mathematics, MDPI, vol. 10(21), pages 1-17, November.
    7. Maryam Esna-Ashari & Mahdi Alimohammadi & Elnaz Garousi & Antonio Di Crescenzo, 2024. "Some New Results on Stochastic Comparisons of Spacings of Generalized Order Statistics from One and Two Samples," Mathematics, MDPI, vol. 12(10), pages 1-19, May.
    8. Ahmed Soliman & N. Abou-elheggag & A. Abd ellah & A. Modhesh, 2012. "Bayesian and non-Bayesian inferences of the Burr-XII distribution for progressive first-failure censored data," METRON, Springer;Sapienza Università di Roma, vol. 70(1), pages 1-25, April.
    9. Stefan Bedbur & Udo Kamps, 2019. "Testing for Equality of Parameters from Different Load-Sharing Systems," Stats, MDPI, vol. 2(1), pages 1-19, January.
    10. Katopodis, Theodoros & Markantonis, Iason & Vlachogiannis, Diamando & Politi, Nadia & Sfetsos, Athanasios, 2021. "Assessing climate change impacts on wind characteristics in Greece through high resolution regional climate modelling," Renewable Energy, Elsevier, vol. 179(C), pages 427-444.
    11. Arthur H.A. Melani & Carlos A. Murad & Adherbal Caminada Netto & Gilberto F.M. Souza & Silvio I. Nabeta, 2019. "Maintenance Strategy Optimization of a Coal-Fired Power Plant Cooling Tower through Generalized Stochastic Petri Nets," Energies, MDPI, vol. 12(10), pages 1-28, May.
    12. M. Hermanns & E. Cramer, 2018. "Inference with progressively censored k-out-of-n system lifetime data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(4), pages 787-810, December.
    13. Balakrishnan, Narayanaswamy & Barmalzan, Ghobad & Haidari, Abedin, 2016. "Multivariate stochastic comparisons of multivariate mixture models and their applications," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 37-43.
    14. Muqrin A. Almuqrin & Mukhtar M. Salah & Essam A. Ahmed, 2022. "Statistical Inference for Competing Risks Model with Adaptive Progressively Type-II Censored Gompertz Life Data Using Industrial and Medical Applications," Mathematics, MDPI, vol. 10(22), pages 1-38, November.
    15. Burkschat Marco & Kamps Udo & Kateri Maria, 2013. "Estimating scale parameters under an order statistics prior," Statistics & Risk Modeling, De Gruyter, vol. 30(3), pages 205-219, August.
    16. Vuong, Q.N. & Bedbur, S. & Kamps, U., 2013. "Distances between models of generalized order statistics," Journal of Multivariate Analysis, Elsevier, vol. 118(C), pages 24-36.
    17. Katzur, Alexander & Kamps, Udo, 2016. "Classification into Kullback–Leibler balls in exponential families," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 75-90.
    18. Vladimir Rykov & Nika Ivanova & Irina Kochetkova, 2022. "Reliability Analysis of a Load-Sharing k -out-of- n System Due to Its Components’ Failure," Mathematics, MDPI, vol. 10(14), pages 1-13, July.
    19. Farha Sultana & Yogesh Mani Tripathi & Shuo-Jye Wu & Tanmay Sen, 2022. "Inference for Kumaraswamy Distribution Based on Type I Progressive Hybrid Censoring," Annals of Data Science, Springer, vol. 9(6), pages 1283-1307, December.
    20. Ritwik Bhattacharya, 2020. "Implementation of compound optimal design strategy in censored life-testing experiment," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(4), pages 1029-1050, 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:spr:metrik:v:83:y:2020:i:4:d:10.1007_s00184-019-00743-4. 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.