IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v78y2008i16p2781-2786.html
   My bibliography  Save this article

Fisher information in hybrid censored data

Author

Listed:
  • Park, Sangun
  • Balakrishnan, N.
  • Zheng, Gang

Abstract

A hybrid censoring is a mixture of Type I and II censoring. Type I and Type II hybrid censoring models are considered in this work. When n items are placed on a life-test, the experiment terminates under the Type I (Type II) hybrid censoring when either the r-th failure (1

Suggested Citation

  • Park, Sangun & Balakrishnan, N. & Zheng, Gang, 2008. "Fisher information in hybrid censored data," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2781-2786, November.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:16:p:2781-2786
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(08)00201-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Sangun Park, 2003. "On the asymptotic Fisher information in order statistics," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 57(1), pages 71-80, February.
    2. Gertsbakh, I., 1995. "On the Fisher information in type-I censored and quantal response data," Statistics & Probability Letters, Elsevier, vol. 23(4), pages 297-306, June.
    3. Kundu, Debasis & Joarder, Avijit, 2006. "Analysis of Type-II progressively hybrid censored data," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2509-2528, June.
    4. Zheng, Gang, 2001. "A characterization of the factorization of hazard function by the Fisher information under Type II censoring with application to the Weibull family," Statistics & Probability Letters, Elsevier, vol. 52(3), pages 249-253, April.
    5. Wang, Yanhua & He, Shuyuan, 2005. "Fisher information in censored data," Statistics & Probability Letters, Elsevier, vol. 73(2), pages 199-206, June.
    6. A. Childs & B. Chandrasekar & N. Balakrishnan & D. Kundu, 2003. "Exact likelihood inference based on Type-I and Type-II hybrid censored samples from the exponential distribution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(2), pages 319-330, June.
    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. Park, Sangun & Balakrishnan, N., 2009. "On simple calculation of the Fisher information in hybrid censoring schemes," Statistics & Probability Letters, Elsevier, vol. 79(10), pages 1311-1319, May.
    2. Balakrishnan, N. & Kundu, Debasis, 2013. "Hybrid censoring: Models, inferential results and applications," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 166-209.

    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. Park, Sangun & Balakrishnan, N., 2009. "On simple calculation of the Fisher information in hybrid censoring schemes," Statistics & Probability Letters, Elsevier, vol. 79(10), pages 1311-1319, May.
    2. Balakrishnan, N. & Kundu, Debasis, 2013. "Hybrid censoring: Models, inferential results and applications," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 166-209.
    3. Wang, Yanhua & He, Shuyuan, 2005. "Fisher information in censored data," Statistics & Probability Letters, Elsevier, vol. 73(2), pages 199-206, June.
    4. George Tzavelas, 2019. "A characterization of the Pareto distribution based on the Fisher information for censored data under non-regularity conditions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(4), pages 429-440, May.
    5. Feizjavadian, S.H. & Hashemi, R., 2015. "Analysis of dependent competing risks in the presence of progressive hybrid censoring using Marshall–Olkin bivariate Weibull distribution," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 19-34.
    6. Ruhul Ali Khan & Murari Mitra, 2021. "Estimation issues in the Exponential–Logarithmic model under hybrid censoring," Statistical Papers, Springer, vol. 62(1), pages 419-450, February.
    7. Ping Chan & Hon Ng & Feng Su, 2015. "Exact likelihood inference for the two-parameter exponential distribution under Type-II progressively hybrid censoring," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(6), pages 747-770, August.
    8. Prakash Chandra & Yogesh Mani Tripathi & Liang Wang & Chandrakant Lodhi, 2023. "Estimation for Kies distribution with generalized progressive hybrid censoring under partially observed competing risks model," Journal of Risk and Reliability, , vol. 237(6), pages 1048-1072, December.
    9. Hassan Okasha & Yuhlong Lio & Mohammed Albassam, 2021. "On Reliability Estimation of Lomax Distribution under Adaptive Type-I Progressive Hybrid Censoring Scheme," Mathematics, MDPI, vol. 9(22), pages 1-38, November.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Park, Sangun & Ng, Hon Keung Tony & Chan, Ping Shing, 2015. "On the Fisher information and design of a flexible progressive censored experiment," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 142-149.
    16. 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.
    17. Tian, Yuzhu & Zhu, Qianqian & Tian, Maozai, 2015. "Estimation for mixed exponential distributions under type-II progressively hybrid censored samples," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 85-96.
    18. Park, Jeong-Soo & Yoon Kim, Tae, 2007. "Fisher information matrix for a four-parameter kappa distribution," Statistics & Probability Letters, Elsevier, vol. 77(13), pages 1459-1466, July.
    19. Deepak Prajapati & Sharmistha Mitra & Debasis Kundu, 2019. "A New Decision Theoretic Sampling Plan for Type-I and Type-I Hybrid Censored Samples from the Exponential Distribution," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 251-288, December.
    20. Suparna Basu & Sanjay K. Singh & Umesh Singh, 2019. "Estimation of Inverse Lindley Distribution Using Product of Spacings Function for Hybrid Censored Data," Methodology and Computing in Applied Probability, Springer, vol. 21(4), pages 1377-1394, December.

    More about this item

    Statistics

    Access and download statistics

    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:eee:stapro:v:78:y:2008:i:16:p:2781-2786. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.