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Statistical inferences based on INID progressively type II censored order statistics

Author

Listed:
  • M. Razmkhah

    (Ferdowsi University of Mashhad)

  • S. Simriz

    (Ferdowsi University of Mashhad)

Abstract

Suppose that the failure times of the units placed on a life-testing experiment are independent but nonidentically distributed random variables. Under progressively type II censoring scheme, distributional properties of the proposed random variables are presented and some inferences are made. Assuming that the random variables come from a proportional hazard rate model, the formulas are simplified and also the amount of Fisher information about the common parameters of this family is calculated. The results are also extended to a fixed covariates model. The performance of the proposed procedure is investigated via a real data set. Some numerical computations are also presented to study the effect of the proportionality rates in view of the Fisher information criterion. Finally, some concluding remarks are stated.

Suggested Citation

  • M. Razmkhah & S. Simriz, 2018. "Statistical inferences based on INID progressively type II censored order statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(3), pages 583-604, June.
    • Handle: RePEc:spr:aistmt:v:70:y:2018:i:3:d:10.1007_s10463-017-0598-9
    DOI: 10.1007/s10463-017-0598-9
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    References listed on IDEAS

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    1. Fischer, T. & Balakrishnan, N. & Cramer, E., 2008. "Mixture representation for order statistics from INID progressive censoring and its applications," Journal of Multivariate Analysis, Elsevier, vol. 99(9), pages 1999-2015, October.
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    3. Mao, Tiantian & Hu, Taizhong, 2010. "Stochastic properties of INID progressive Type-II censored order statistics," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1493-1500, July.
    4. N. Balakrishnan, 2007. "Rejoinder 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 290-296, August.
    5. N. Balakrishnan & Erhard Cramer, 2008. "Progressive censoring from heterogeneous distributions with applications to robustness," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(1), pages 151-171, March.
    6. M. Rezapour & M.H. Alamatsaz & N. Balakrishnan, 2013. "On properties of dependent progressively Type-II censored order statistics," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(7), pages 909-917, October.
    7. Burkschat, M. & Cramer, E. & Kamps, U., 2006. "On optimal schemes in progressive censoring," Statistics & Probability Letters, Elsevier, vol. 76(10), pages 1032-1036, May.
    8. Balakrishnan, N. & Burkschat, Marco & Cramer, Erhard & Hofmann, Glenn, 2008. "Fisher information based progressive censoring plans," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 366-380, December.
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