IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v65y2024i3d10.1007_s00362-023-01417-0.html
   My bibliography  Save this article

Inference of improved adaptive progressively censored competing risks data for Weibull lifetime models

Author

Listed:
  • Ahmed Elshahhat

    (Zagazig University)

  • Mazen Nassar

    (King Abdulaziz University
    Zagazig University)

Abstract

Recently, an improved adaptive Type-II progressive censoring scheme is proposed to ensure that the experimental time will not pass a pre-fixed time and ends the test after recording a pre-fixed number of failures. This paper studies the inference of the competing risks model from Weibull distribution under the improved adaptive progressive Type-II censoring. For this goal, we used the latent failure time model with Weibull lifetime distributions with common shape parameters. The point and interval estimation problems of parameters, reliability and hazard rate functions using the maximum likelihood and Bayesian estimation methods are considered. Moreover, making use of the asymptotic normality of classical estimators and delta method, approximate intervals are constructed via the observed Fisher information matrix. Following the assumption of independent gamma priors, the Bayes estimates of the scale parameters have closed expressions, but when the common shape parameter is unknown, the Bayes estimates cannot be formed explicitly. To solve this difficulty, we recommend using Markov chain Monte Carlo routine to compute the Bayes estimates and to construct credible intervals. A comprehensive Monte Carlo simulation is conducted to judge the behavior of the offered methods. Ultimately, analysis of electrodes data from the life-test of high-stress voltage endurance is provided to illustrate all proposed inferential procedures.

Suggested Citation

  • Ahmed Elshahhat & Mazen Nassar, 2024. "Inference of improved adaptive progressively censored competing risks data for Weibull lifetime models," Statistical Papers, Springer, vol. 65(3), pages 1163-1196, May.
    • Handle: RePEc:spr:stpapr:v:65:y:2024:i:3:d:10.1007_s00362-023-01417-0
    DOI: 10.1007/s00362-023-01417-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00362-023-01417-0
    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/s00362-023-01417-0?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. Essam A. Ahmed & Ziyad Ali Alhussain & Mukhtar M. Salah & Hanan Haj Ahmed & M. S. Eliwa, 2020. "Inference of progressively type-II censored competing risks data from Chen distribution with an application," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(13-15), pages 2492-2524, November.
    2. S. K. Ashour & M. Nassar, 2017. "Inference for Weibull distribution under adaptive Type-I progressive hybrid censored competing risks data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(10), pages 4756-4773, May.
    3. Xiaolin Shi & Yanchao Liu & Yimin Shi, 2017. "Statistical analysis for masked hybrid system lifetime data in step-stress partially accelerated life test with progressive hybrid censoring," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-15, October.
    4. Hon Keung Tony Ng & Debasis Kundu & Ping Shing Chan, 2009. "Statistical analysis of exponential lifetimes under an adaptive Type‐II progressive censoring scheme," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(8), pages 687-698, December.
    5. Mazen Nassar & Refah Alotaibi & Chunfang Zhang, 2022. "Estimation of Reliability Indices for Alpha Power Exponential Distribution Based on Progressively Censored Competing Risks Data," Mathematics, MDPI, vol. 10(13), pages 1-25, June.
    6. Junru Ren & Wenhao Gui, 2021. "Inference and optimal censoring scheme for progressively Type-II censored competing risks model for generalized Rayleigh distribution," Computational Statistics, Springer, vol. 36(1), pages 479-513, March.
    7. Ahmed Elshahhat & Mazen Nassar, 2021. "Bayesian survival analysis for adaptive Type-II progressive hybrid censored Hjorth data," Computational Statistics, Springer, vol. 36(3), pages 1965-1990, September.
    8. Debasis Kundu & Rameshwar Gupta, 2007. "Analysis of Hybrid Life-tests in Presence of Competing Risks," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 65(2), pages 159-170, February.
    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. Subhankar Dutta & Sanku Dey & Suchandan Kayal, 2024. "Bayesian survival analysis of logistic exponential distribution for adaptive progressive Type-II censored data," Computational Statistics, Springer, vol. 39(4), pages 2109-2155, June.
    2. 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.
    3. Abdalla Abdel-Ghaly & Hanan Aly & Elham Abdel-Rahman, 2023. "Bayesian Inference Under Ramp Stress Accelerated Life Testing Using Stan," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 132-174, May.
    4. Ahmed Elshahhat & Refah Alotaibi & Mazen Nassar, 2022. "Inferences for Nadarajah–Haghighi Parameters via Type-II Adaptive Progressive Hybrid Censoring with Applications," Mathematics, MDPI, vol. 10(20), pages 1-19, October.
    5. Kundan Singh & Yogesh Mani Tripathi & Liang Wang & Shuo-Jye Wu, 2024. "Analysis of Block Adaptive Type-II Progressive Hybrid Censoring with Weibull Distribution," Mathematics, MDPI, vol. 12(24), pages 1-21, December.
    6. O. E. Abo-Kasem & Ehab M. Almetwally & Wael S. Abu El Azm, 2023. "Inferential Survival Analysis for Inverted NH Distribution Under Adaptive Progressive Hybrid Censoring with Application of Transformer Insulation," Annals of Data Science, Springer, vol. 10(5), pages 1237-1284, October.
    7. Refah Alotaibi & Mazen Nassar & Ahmed Elshahhat, 2022. "Computational Analysis of XLindley Parameters Using Adaptive Type-II Progressive Hybrid Censoring with Applications in Chemical Engineering," Mathematics, MDPI, vol. 10(18), pages 1-24, September.
    8. Refah Alotaibi & Mazen Nassar & Hoda Rezk & Ahmed Elshahhat, 2022. "Inferences and Engineering Applications of Alpha Power Weibull Distribution Using Progressive Type-II Censoring," Mathematics, MDPI, vol. 10(16), pages 1-21, August.
    9. E. M. Almetwally & H. M. Almongy & M. K. Rastogi & M. Ibrahim, 2020. "Maximum Product Spacing Estimation of Weibull Distribution Under Adaptive Type-II Progressive Censoring Schemes," Annals of Data Science, Springer, vol. 7(2), pages 257-279, June.
    10. Refah Alotaibi & Ehab M. Almetwally & Qiuchen Hai & Hoda Rezk, 2022. "Optimal Test Plan of Step Stress Partially Accelerated Life Testing for Alpha Power Inverse Weibull Distribution under Adaptive Progressive Hybrid Censored Data and Different Loss Functions," Mathematics, MDPI, vol. 10(24), pages 1-24, December.
    11. Wenjie Zhang & Wenhao Gui, 2022. "Statistical Inference and Optimal Design of Accelerated Life Testing for the Chen Distribution under Progressive Type-II Censoring," Mathematics, MDPI, vol. 10(9), pages 1-21, May.
    12. Yajie Tian & Wenhao Gui, 2024. "Inference and expected total test time for step-stress life test in the presence of complementary risks and incomplete data," Computational Statistics, Springer, vol. 39(2), pages 1023-1060, April.
    13. El-Sayed A. El-Sherpieny & Hiba Z. Muhammed & Ehab M. Almetwally, 2024. "Data Analysis by Adaptive Progressive Hybrid Censored Under Bivariate Model," Annals of Data Science, Springer, vol. 11(2), pages 507-548, April.
    14. Siyi Chen & Wenhao Gui, 2020. "Statistical Analysis of a Lifetime Distribution with a Bathtub-Shaped Failure Rate Function under Adaptive Progressive Type-II Censoring," Mathematics, MDPI, vol. 8(5), pages 1-21, April.
    15. Siqi Chen & Wenhao Gui, 2020. "Estimation of Unknown Parameters of Truncated Normal Distribution under Adaptive Progressive Type II Censoring Scheme," Mathematics, MDPI, vol. 9(1), pages 1-33, December.
    16. Arnab Koley & Debasis Kundu, 2017. "On generalized progressive hybrid censoring in presence of competing risks," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(4), pages 401-426, May.
    17. Mazen Nassar & Refah Alotaibi & Chunfang Zhang, 2022. "Estimation of Reliability Indices for Alpha Power Exponential Distribution Based on Progressively Censored Competing Risks Data," Mathematics, MDPI, vol. 10(13), pages 1-25, June.
    18. Subhankar Dutta & Suchandan Kayal, 2023. "Inference of a competing risks model with partially observed failure causes under improved adaptive type-II progressive censoring," Journal of Risk and Reliability, , vol. 237(4), pages 765-780, August.
    19. Ahmed Elshahhat & Mazen Nassar, 2021. "Bayesian survival analysis for adaptive Type-II progressive hybrid censored Hjorth data," Computational Statistics, Springer, vol. 36(3), pages 1965-1990, September.
    20. Ahmed Elshahhat & Osama E. Abo-Kasem & Heba S. Mohammed, 2023. "Survival Analysis of the PRC Model from Adaptive Progressively Hybrid Type-II Censoring and Its Engineering Applications," Mathematics, MDPI, vol. 11(14), pages 1-26, July.

    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:stpapr:v:65:y:2024:i:3:d:10.1007_s00362-023-01417-0. 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.