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Parameter estimations for generalized exponential distribution under progressive type-I interval censoring

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  • Chen, D.G.
  • Lio, Y.L.

Abstract

The estimates, via maximum likelihood, moment method and probability plot, of the parameters in the generalized exponential distribution under progressive type-I interval censoring are studied. A simulation is conducted to compare these estimates in terms of mean squared errors and biases. Finally, these estimate methods are applied to a real data set based on patients with plasma cell myeloma in order to demonstrate the applicabilities.

Suggested Citation

  • Chen, D.G. & Lio, Y.L., 2010. "Parameter estimations for generalized exponential distribution under progressive type-I interval censoring," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1581-1591, June.
  • Handle: RePEc:eee:csdana:v:54:y:2010:i:6:p:1581-1591
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    1. Carrasco, Jalmar M.F. & Ortega, Edwin M.M. & Cordeiro, Gauss M., 2008. "A generalized modified Weibull distribution for lifetime modeling," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 450-462, December.
    2. Kundu, Debasis & Raqab, Mohammad Z., 2005. "Generalized Rayleigh distribution: different methods of estimations," Computational Statistics & Data Analysis, Elsevier, vol. 49(1), pages 187-200, April.
    3. C. D. Kemp & Adrienne W. Kemp, 1987. "Rapid Generation of Frequency Tables," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(3), pages 277-282, November.
    4. Wang, Zhihui & Desmond, A.F. & Lu, Xuewen, 2006. "Modified censored moment estimation for the two-parameter Birnbaum-Saunders distribution," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 1033-1051, February.
    5. Gupta, Rameshwar D. & Kundu, Debasis, 2003. "Discriminating between Weibull and generalized exponential distributions," Computational Statistics & Data Analysis, Elsevier, vol. 43(2), pages 179-196, June.
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    Cited by:

    1. Yu-Jau Lin & Y. L. Lio, 2012. "Bayesian inference under progressive type-I interval censoring," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(8), pages 1811-1824, April.
    2. Soumya Roy & Biswabrata Pradhan, 2023. "Inference for log‐location‐scale family of distributions under competing risks with progressive type‐I interval censored data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 77(2), pages 208-232, May.
    3. Saralees Nadarajah, 2011. "The exponentiated exponential distribution: a survey," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(3), pages 219-251, September.
    4. Sonal Budhiraja & Biswabrata Pradhan, 2020. "Point and interval estimation under progressive type-I interval censoring with random removal," Statistical Papers, Springer, vol. 61(1), pages 445-477, February.
    5. Sukhdev Singh & Yogesh Mani Tripathi, 2018. "Estimating the parameters of an inverse Weibull distribution under progressive type-I interval censoring," Statistical Papers, Springer, vol. 59(1), pages 21-56, March.
    6. 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.
    7. Wu, Shuo-Jye & Huang, Syuan-Rong, 2012. "Progressively first-failure censored reliability sampling plans with cost constraint," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2018-2030.
    8. Wu, Shuo-Jye & Hsu, Chu-Chun & Huang, Syuan-Rong, 2020. "Optimal designs and reliability sampling plans for one-shot devices with cost considerations," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    9. David Han & Debasis Kundu, 2013. "Inference for a step-stress model with competing risks from the GE distribution under Type-I censoring," Working Papers 0181mss, College of Business, University of Texas at San Antonio.
    10. 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.
    11. Budhiraja, Sonal & Pradhan, Biswabrata & Sengupta, Debasis, 2017. "Maximum likelihood estimators under progressive Type-I interval censoring," Statistics & Probability Letters, Elsevier, vol. 123(C), pages 202-209.
    12. Refah Alotaibi & Hoda Rezk & Sanku Dey & Hassan Okasha, 2021. "Bayesian estimation for Dagum distribution based on progressive type I interval censoring," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-17, June.
    13. Mahdi Teimouri, 2022. "bccp: an R package for life-testing and survival analysis," Computational Statistics, Springer, vol. 37(1), pages 469-489, March.
    14. Saieed Ateya, 2014. "Maximum likelihood estimation under a finite mixture of generalized exponential distributions based on censored data," Statistical Papers, Springer, vol. 55(2), pages 311-325, May.

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