IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v54y2013i3p619-643.html
   My bibliography  Save this article

Inference on unknown parameters of a Burr distribution under hybrid censoring

Author

Listed:
  • Manoj Rastogi
  • Yogesh Tripathi

Abstract

Based on hybrid censored data, the problem of making statistical inference on parameters of a two parameter Burr Type XII distribution is taken up. The maximum likelihood estimates are developed for the unknown parameters using the EM algorithm. Fisher information matrix is obtained by applying missing value principle and is further utilized for constructing the approximate confidence intervals. Some Bayes estimates and the corresponding highest posterior density intervals of the unknown parameters are also obtained. Lindley’s approximation method and a Markov Chain Monte Carlo (MCMC) technique have been applied to evaluate these Bayes estimates. Further, MCMC samples are utilized to construct the highest posterior density intervals as well. A numerical comparison is made between proposed estimates in terms of their mean square error values and comments are given. Finally, two data sets are analyzed using proposed methods. Copyright Springer-Verlag 2013

Suggested Citation

  • Manoj Rastogi & Yogesh Tripathi, 2013. "Inference on unknown parameters of a Burr distribution under hybrid censoring," Statistical Papers, Springer, vol. 54(3), pages 619-643, August.
    • Handle: RePEc:spr:stpapr:v:54:y:2013:i:3:p:619-643
    DOI: 10.1007/s00362-012-0452-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00362-012-0452-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00362-012-0452-3?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. M. Mousa & Z. Jaheen, 2002. "Bayesian prediction for progressively censored data from the Burr model," Statistical Papers, Springer, vol. 43(4), pages 587-593, October.
    2. Ng, H. K. T. & Chan, P. S. & Balakrishnan, N., 2002. "Estimation of parameters from progressively censored data using EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 39(4), pages 371-386, June.
    3. Dallas Wingo, 1993. "Maximum likelihood methods for fitting the burr type XII distribution to multiply (progressively) censored life test data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 40(1), pages 203-210, December.
    4. Min Kim & Bong-Jin Yum, 2011. "Life test sampling plans for Weibull distributed lifetimes under accelerated hybrid censoring," Statistical Papers, Springer, vol. 52(2), pages 327-342, May.
    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. 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.
    2. Saieed F. Ateya & Abdulaziz S. Alghamdi & Abd Allah A. Mousa, 2022. "Future Failure Time Prediction Based on a Unified Hybrid Censoring Scheme for the Burr-X Model with Engineering Applications," Mathematics, MDPI, vol. 10(9), pages 1-23, April.
    3. Rastogi, Manoj Kumar & Tripathi, Yogesh Mani, 2013. "Estimation using hybrid censored data from a two-parameter distribution with bathtub shape," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 268-281.
    4. M. Noori Asl & R. Arabi Belaghi & H. Bevrani, 2017. "On Burr XII Distribution Analysis Under Progressive Type-II Hybrid Censored Data," Methodology and Computing in Applied Probability, Springer, vol. 19(2), pages 665-683, June.
    5. Tanmay Sen & Yogesh Mani Tripathi & Ritwik Bhattacharya, 2018. "Statistical Inference and Optimum Life Testing Plans Under Type-II Hybrid Censoring Scheme," Annals of Data Science, Springer, vol. 5(4), pages 679-708, December.
    6. R. Arabi Belaghi & M. Noori Asl, 2019. "Estimation based on progressively type-I hybrid censored data from the Burr XII distribution," Statistical Papers, Springer, vol. 60(3), pages 761-803, June.

    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. Sukhdev Singh & Yogesh Tripathi, 2015. "Reliability sampling plans for a lognormal distribution under progressive first-failure censoring with cost constraint," Statistical Papers, Springer, vol. 56(3), pages 773-817, August.
    2. M. Noori Asl & R. Arabi Belaghi & H. Bevrani, 2017. "On Burr XII Distribution Analysis Under Progressive Type-II Hybrid Censored Data," Methodology and Computing in Applied Probability, Springer, vol. 19(2), pages 665-683, June.
    3. Balakrishnan, N. & Mitra, Debanjan, 2012. "Left truncated and right censored Weibull data and likelihood inference with an illustration," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4011-4025.
    4. Amit Singh Nayal & Bhupendra Singh & Vrijesh Tripathi & Abhishek Tyagi, 2024. "Analyzing stress-strength reliability $$\delta =\text{ P }[U," 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. 15(6), pages 2453-2472, June.
    5. Abdel-Hamid, Alaa H., 2009. "Constant-partially accelerated life tests for Burr type-XII distribution with progressive type-II censoring," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2511-2523, May.
    6. Manoj Kumar & Sanjay Kumar Singh & Umesh Singh, 2018. "Bayesian inference for Poisson-inverse exponential distribution under progressive type-II censoring with binomial removal," 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. 9(6), pages 1235-1249, December.
    7. Balakrishnan, N. & Saleh, H.M., 2011. "Relations for moments of progressively Type-II censored order statistics from half-logistic distribution with applications to inference," Computational Statistics & Data Analysis, Elsevier, vol. 55(10), pages 2775-2792, October.
    8. Wu, Shuo-Jye & Kus, Coskun, 2009. "On estimation based on progressive first-failure-censored sampling," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3659-3670, August.
    9. Rana Muhammad Usman & Maryam Ilyas, 2024. "Power Burr X-T family of distributions: properties, estimation methods and real-life applications," Computational Statistics, Springer, vol. 39(6), pages 2949-2974, September.
    10. Altındağ, Ömer & Aydoğdu, Halil, 2021. "Estimation of renewal function under progressively censored data and its applications," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    11. Y. L. Lio & Tzong-Ru Tsai, 2012. "Estimation of δ= P ( X > Y ) for Burr XII distribution based on the progressively first failure-censored samples," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 309-322, April.
    12. Valiollahi, R. & Raqab, Mohammad Z. & Asgharzadeh, A. & Alqallaf, F.A., 2018. "Estimation and prediction for power Lindley distribution under progressively type II right censored samples," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 149(C), pages 32-47.
    13. Kousik Maiti & Suchandan Kayal, 2023. "Estimating Reliability Characteristics of the Log-Logistic Distribution Under Progressive Censoring with Two Applications," Annals of Data Science, Springer, vol. 10(1), pages 89-128, February.
    14. Xun Xiao & Amitava Mukherjee & Min Xie, 2016. "Estimation procedures for grouped data – a comparative study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(11), pages 2110-2130, August.
    15. Basak, Prasanta & Basak, Indrani & Balakrishnan, N., 2009. "Estimation for the three-parameter lognormal distribution based on progressively censored data," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3580-3592, August.
    16. Soumya Roy & Chiranjit Mukhopadhyay, 2015. "Maximum likelihood analysis of multi-stress accelerated life test data of series systems with competing log-normal causes of failure," Journal of Risk and Reliability, , vol. 229(2), pages 119-130, April.
    17. Shahsanaei Fatemeh & Rezaei Sadegh & Pak Abbas, 2012. "A New Two-Parameter Lifetime Distribution with Increasing Failure Rate," Stochastics and Quality Control, De Gruyter, vol. 27(1), pages 1-17, September.
    18. M. El-Din & A. Shafay, 2013. "One- and two-sample Bayesian prediction intervals based on progressively Type-II censored data," Statistical Papers, Springer, vol. 54(2), pages 287-307, May.
    19. Park, Sangun & Ng, Hon Keung Tony, 2012. "Missing information and an optimal one-step plan in a Type II progressive censoring scheme," Statistics & Probability Letters, Elsevier, vol. 82(2), pages 396-402.
    20. Ji Hwan Cha & Maxim Finkelstein, 2023. "Acceptance reliability sampling plan for items from heterogeneous populations," Journal of Risk and Reliability, , vol. 237(6), pages 1199-1208, 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:stpapr:v:54:y:2013:i:3:p:619-643. 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.