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An efficient computational method for moments of order statistics under progressive censoring

Author

Listed:
  • Balakrishnan, N.
  • Childs, A.
  • Chandrasekar, B.

Abstract

Thomas and Wilson (Technometrics 14 (1972) 679) developed a computational method for calculating the single and product moments of order statistics from progressively censored samples by making use of the corresponding moments of the usual order statistics. The absence of an explicit representation for the marginal and joint density function of order statistics under progressive censoring makes their method extremely tedious. By deriving the required marginal and joint density functions in explicit form, we obtain an alternative, highly efficient, method for computing the desired moments.

Suggested Citation

  • Balakrishnan, N. & Childs, A. & Chandrasekar, B., 2002. "An efficient computational method for moments of order statistics under progressive censoring," Statistics & Probability Letters, Elsevier, vol. 60(4), pages 359-365, December.
    • Handle: RePEc:eee:stapro:v:60:y:2002:i:4:p:359-365
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    Citations

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    Cited by:

    1. U. H. Salemi & S. Rezaei & Y. Si & S. Nadarajah, 2018. "On Optimal Progressive Censoring Schemes for Normal Distribution," Annals of Data Science, Springer, vol. 5(4), pages 637-658, December.
    2. Chunfang Zhang & Yimin Shi, 2017. "Optimum simple accelerated life tests based on progressively Type-I hybrid censoring," 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. 8(2), pages 849-856, November.
    3. Haikady Nagaraja, 2007. "Comments on: Progressive censoring methodology: an appraisal," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(2), pages 260-261, August.
    4. Basak, Indrani & Basak, Prasanta & Balakrishnan, N., 2006. "On some predictors of times to failure of censored items in progressively censored samples," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1313-1337, March.
    5. 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.
    6. 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.
    7. M. M. Mohie El-Din & A. R. Shafay & M. Nagy, 2018. "Statistical inference under adaptive progressive censoring scheme," Computational Statistics, Springer, vol. 33(1), pages 31-74, March.
    8. Ayman M. Abd-Elrahman & Khalaf S. Sultan, 2007. "Reliability estimation based on general progressive censored data from theWeibull model: comparison between Bayesian and classical approaches," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 239-257.
    9. Jung-In Seo & Suk-Bok Kang, 2016. "An objective Bayesian analysis of the two-parameter half-logistic distribution based on progressively type-II censored samples," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(12), pages 2172-2190, September.
    10. Kotb, M.S. & Raqab, M.Z., 2019. "Statistical inference for modified Weibull distribution based on progressively type-II censored data," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 162(C), pages 233-248.
    11. Lin, Chien-Tai & Chou, Cheng-Chieh & Huang, Yen-Lung, 2012. "Inference for the Weibull distribution with progressive hybrid censoring," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 451-467.
    12. 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.
    13. Bairamov, Ismihan, 2006. "Progressive Type II censored order statistics for multivariate observations," Journal of Multivariate Analysis, Elsevier, vol. 97(4), pages 797-809, April.
    14. Arnab Koley & Debasis Kundu, 2021. "Analysis of progressive Type‐II censoring in presence of competing risk data under step stress modeling," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(2), pages 115-136, May.

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